System, Method and Apparatus for Electronically Searching for an Item

ABSTRACT

The present invention provides a system, method and apparatus for electronically searching for an item by receiving a search request comprising a requested category and one or more requested attributes of the item and storing the search request in a search index based on the requested category and the requested attribute(s). The search index includes one or more categories and each category is defined by a taxonomy of attributes. The search index is then searched for any previously stored search requests that match the requested category and the requested attribute(s), a result of the search is determined and a search response that includes the result of the search is sent.

PRIORITY CLAIM

This patent application is a continuation application of U.S. patentapplication Ser. No. 11/321,155 filed on Dec. 28, 2005, now U.S. Pat.No. 8,364,670, entitled “System, Method and Apparatus for ElectronicallySearching for an Item”, which is a non-provisional application of U.S.patent application 60/640,156 filed on Dec. 28, 2004, both of which arehereby incorporated by reference in their entirety.

The patent application is related to U.S. patent application Ser. No.13/598,348 filed on Aug. 29, 2012 entitled “System, Method and Apparatusfor Electronically Searching for an Item”.

FIELD OF THE INVENTION

The present invention relates generally to the field of computerizedinformation retrieval and, more particularly, to a system, method andapparatus for electronically searching for an item.

BACKGROUND OF THE INVENTION

With a budget of more than $5 billion, Proctor & Gamble is the world'slargest advertiser. It is very bad news for network TV when its P&G'sGlobal Marketing Officer Jim Spangle says that today's marketing modelis broken. This can be seen everywhere. Over the last ten years,American Express has reduced its TV network spending from 80% of itsbudget to under 30%. This trend can be seen in virtually every category.

A business model that has worked of over 50 years is slowly collapsing.Over the last decade, Nielsen reports that network TV has seen itsaudience decline 20% when the U.S. population actually grew by 30million. During this time, the advertising cost to reach buyers hasnearly tripled.

How bad will it get? A glimpse of the future can be seen in today'stech-savvy males aged 18-32. For them, traditional advertising is acomplete waste of money. A Wired Magazine article documented how theyare virtually impossible to market to. The article was called “The LostBoys.”

Where will the estimated $75 billion in annual network TV advertisingend up? Amex CMO John Hayes says that there is no immediate place toredirect ad budgets but warns that “those who are unprepared for changewill obviously suffer the consequences.” Forrester Research's ChrisSharon warns that network TV have a lot at stake in the status quo, soit will not be fast to look elsewhere. David Poltrack, head of researchat CBS, believes that if advertisers and marketers abandon network TV,the “entire marketing infrastructure of the country and the economy isgoing to be diminished.” Not surprisingly, Viacom is looking at ways tospin-off CBS.

Viacom is not alone. Rupert Murdock's News Corp commissioned McKinsey &Company to figure out how to transition from network TV to the Internet.In August 2005, News Corp reported plans to create a major portal andexpand on the Internet. Murdoch said, “There is no greater priority forthe company today” and announced plans to spend about “$2 billion onInternet acquisitions.”

Jupiter Research predicts that online advertising will overtake magazineadvertising in 2007 when total online ad spending hits $13.8 billion, or6% of offline ad spending. The CEO of the Direct Marketing Associationput it bluntly when he said it is at a “critical juncture in itshistory”.

With respect to Internet search engines, billions of dollars are alreadybeing redirected to the Internet, and firms want to benefit from this inthe same way as Google has. Google now has a market valuation of morethan four times Ford and General Motors combined. The reason why searchengine companies are so hot is simple—70% of online purchases start witha search. Thousands of search engine marketing (SEM) companies haveappeared almost overnight to help advertisers place these billions ofredirected dollars. The most powerful eCommerce brands are now investingheavily in search technologies so that they can claim their share ofthis 70%.

As shown in FIG. 1, typical search engine technologies 100 in accordancewith the prior art use keyword search engines 102 that include a keywordsearch index 104 communicably coupled to a data storage 106 andsponsored links 108. The keyword search index 104 is populated withterms used by buyers 110 when conducting a search. The keyword searchengine 102 scours the Internet (World Wide Web) 112 for documents or webpages that contain the keywords. The documents, web pages or relevantdata to link or point to such document and web pages are stored in datastorage 106, which is used to further populate the keyword search index104. The searching, storing, selecting mechanisms are extremelycomplicated and require massive data storage and processing power.Sellers 114 typically purchase the option to have their sponsored links108 included in the search results provided to buyer 110 based onvarious criteria. As a result, advertising drive current search enginetechnologies.

In spite of their recent success, current search engine technologiesstill leave lots of room for improvement:

-   -   98% of Google's revenue comes from advertising, and an estimated        10-30% of it is from “click fraud” where people intentionally        click on ads to drain rival company budgets. Google's CFO said,        “Something has to be done about this really, really quickly,        because I think, potentially, it threatens our business model”.    -   New search engine technologies are often wasted. When Google        introduced its desktop search capability, its rivals launched        free copycat services. Technologies (1) with no direct revenue        models that (2) can be copied are great for users but have a        smaller impact on profitability and differentiation.    -   New, unique technologies need to be defensible. No firm wants to        be the next Netscape—a firm that was specifically targeted and        quickly crushed by Microsoft.    -   Current technologies are wasteful. When Yahoo announced that it        had indexed billions more Web pages than Google, search engine        expert Danny Sullivan said, “Screw size! I dare Google & Yahoo        to report on relevancy . . . You need the whole haystack! Here,        if I dump it all on your head, can you find the needle now?”    -   Search engine relevancy is becoming a key goal for all brands.        In October 2005, Microsoft CEO Steve Balmer said “50% of all        searches do not go to desired outcome . . . people can't find        what they are looking for . . . relevance is job one.”    -   Search engine relevance is currently based on complex algorithms        that try to anticipate and analyze what a person wants. These        continue to get more complex with diminishing improvements.    -   To improve relevance, search engine technologies attempt to        capture more and more personal information. This is inconsistent        with what people want because of increased fraud and identity        theft, which is now the fastest growing crime in America.    -   The new industry of Search Engine Marketing (SEM) firms now        manipulates search results to satisfy the needs of the        advertiser and not the buyer. The best “sponsored links” are        generally sold to advertisers that pay the most money. The        ranking of “organic” search results can also be manipulated to        the point where the search results have little to do with what        was requested. Not at all buyer-centric.    -   The amount of feedback and marketing information available to        advertisers is limited. There is currently no way to measure or        act upon partial interest by measuring “close hits” or “lost        sales.”    -   Current technologies do not respect the time of the consumer        because the results are often not relevant. Clicking on a link        often leads to more time searching a Website.    -   Current search engine technologies do not maximize the        Internet's full potential because they do not give Sellers        proactive tools. They still have to wait for a Buyer to click on        a sponsored link or organic listing. This is the business        equivalent to a teenage girl sitting by the phone waiting for        her boyfriend to call.

The last two points are worth further explanation with the typicalGoogle search result. For example, FIG. 2 is an example of a userinterface and search result in accordance with the prior art. It istypical for Google to return a bewildering array of more than 6 millionresults 200. The “organic” results 202 are on the left and the“sponsored links” 204 are on the top left and on the right. Ninety-eightpercent of Google's revenue comes from these sponsored links 204.Thousands of SEM companies help advertisers position themselves close tothe top of organic 202 and sponsored search results 204 to increase thelikelihood of being noticed by the buyer.

Eye-tracking technologies illustrate what gets noticed:

-   -   The sponsored links above the organic listing gets some.    -   The first three organic listings on the left get the most.    -   The sponsored links on the right get fewer results.    -   People don't go down the results very far.        These studies reveal show that people do not want to spend lots        of time searching, and advertisers are 100% dependent on being        found by the person. What is needed is a new type of search        engine technology that solves these problems.

With advertising, there is a delicate balance between what is good for aconsumer and what is good for an advertiser. For example, what is goodfor a consumer is almost always bad for an advertiser, and visa versa:

-   -   80 million people have signed up for the Do Not Call list, but        this has hurt the telemarketing industry.    -   Spam is incredibly cost-efficient, but alienates consumers.    -   Privacy policies and trust seals from firms like BBBOnline and        TRUSTe were supposed to protect consumers, but have been reduced        to legal disclaimers that protect companies.    -   Accurate personalization can increase click-through rates, but        collecting the necessary information can be intrusive.    -   Advertising reduced prices are almost always used to attract new        consumers, but this erodes margins and attracts the least loyal        consumers.        What is needed is a new search engine technology that creates a        win-win for both consumers and advertisers.

Current search engine technologies have specific flaws. From aneCommerce perspective, current search engine technologies use the basicdesign shown in FIG. 1. While hugely profitable, this design hassignificant problems:

-   -   Sellers create a Website, with the possible help from Search        Engine Marketing (SEM) companies. These companies attempt to        manipulate the algorithms used by a search engine when it ranks        “organic” search results. This manipulation is good for Sellers        and not good for Buyers.    -   This, along with billions of other Web pages, are “scraped” or        “crawled” by the search engine and put into Data Storage and        Search Index for later access. Billions of Web pages are        analyzed and it is estimated that Google requires over 150,000        servers to complete searches by sheer brute force:    -   On average, a single query reads hundreds of megabytes of data        and consumes tens of billions of CPU cycles.    -   Google's PageRank algorithm performs an objective measurement of        the importance of Webpages by solving an equation of more than        500 million variables and 2 billion terms.    -   At this scale, some limits of massive server parallelism become        apparent, such as the limited cooling capacity of commercial        data centers.    -   Sellers, with the possible help of SEM companies, use their        advertising budgets to pay for Sponsored Links that are also        added to the Search Index. The manipulation is dependent on the        amount of money the Seller is willing to pay, whether or not the        Seller's offer has anything to do with what the Buyer wants.        This again is good for Sellers and not good for Buyers.    -   Sellers must wait for a Buyer to type a specific keyword.        Nothing happens until then, which is not good for Sellers.    -   The search engine does not know in advance what the Buyer wants,        so when the Buyer types one or more keywords, the search engine        must have sufficient hardware and complex algorithms to return        the results quickly. According to Urs Hoelzle, Google's Google's        VP of Engineering, “exactly what will be searched for on any        given day is never predictable [so] keeping the 10 billion pages        of the Web close at hand is a daunting challenge.”    -   The search results have more to do with the Seller's        manipulation than the Buyer's needs. This lack of relevance,        plus the hundreds, thousands, or even millions of results, make        analysis of the search results complex, which is not good for        the Buyer.    -   Some search engines technologies use behavioral and/or tracking        methods to attempt to increase the relevance of the search        results for the Buyer. This potentially invades the privacy of        the Buyer.    -   If the Buyer clicks on an organic link in the Search Index,        control is passed to the Seller's Website. Once there, the Buyer        is left to navigate the Website with no additional help. This        can be very time consuming. In some cases, the Buyer must        register or answer personal questions to get the desired        information from the Seller.    -   If the Buyer clicks on a sponsored link in the Search Index, the        Seller is charged a fee and control is passed to the Seller's        Website. It is possible for anyone to click on a link, and the        resulting “click fraud” hurts both the Seller and the search        ending company. Again, the Buyer must navigate the Website to        find the desired information.    -   If the Buyer does not click on an organic or sponsored link, the        Buyer has little or no marketing intelligence to help learn from        the event. There is no way to quantify a “close hit” or “lost        sale.” The Seller is in a very limited react mode.

Accordingly there is a need for a system, method and apparatus forelectronically searching for an item that provides relevant searchresults, persistent searching and protects the privacy of its users.

SUMMARY OF THE INVENTION

The present invention provides a system, method and apparatus forelectronically searching for an item that provides relevant searchresults, persistent searching and protects the privacy of its users. Forexample, the present invention reduces:

-   -   Dependency that Search Engine companies have on advertising        revenue. In doing so, this will also reduce click fraud. This        will enable Search Engine companies to earn more revenue by        providing more value to Sellers.    -   The need to store billions of irrelevant Web pages. This will        enable Search Engine companies to spend less on the cost of        collecting and managing information that has little or no value.    -   The need to collect personal information from Buyers and        possibly even Sellers. Not collecting personal information        builds trust because it reduces or eliminates the chance that it        will be disclosed to the wrong party or abused in any way.    -   The time required to find the desired item. This does much more        than make the search process easier for the Buyer. It is well        known that a Seller must save a Buyer either time or money.        Reducing the time to find the right product or service permits        Sellers to charge a premium price. This protects Seller margins.    -   The need to continue searching at a linked Website. This again        benefits both the Buyer by saving them time and the Seller by        protecting their margins.    -   The need for manipulating search results. This permits Buyers to        find products and services based on Buyer needs without        interference or comment from any other party.    -   Cluttered, irrelevant results. This permits Buyers to quickly        assess search results that are ranked by their own relevancy.

Moreover, the present invention increases:

-   -   Relevance without more and more complex algorithms. This        benefits all parties because Buyers and Sellers can find each        other based on common interests in a clear and concise manner.    -   Marketing information for advertisers, such as capturing “close        hit” data from partial interest, and “lost sales” data from a        Buyer that decided to continue with another Seller. This permits        Sellers to learn from mistakes and position their products and        services in a more efficient manner, even when the desired        results are not achieved.    -   Tools so Sellers can be more pro-active and not just wait for        Buyers. This permits Sellers to take the initiative in locating        Buyers in a proactive manner that does not violate the privacy        of either party.    -   Tools to get product and service information directly from        Seller legacy systems instead of having to “scrape” it from        Seller Websites.    -   Knowing in advance what Buyers and Sellers want.

Moreover, the present invention makes it extremely easy for a Buyer tospecify what they are looking for anywhere, anytime, and they controlthe final part of the searching and shopping process.

The present invention provides a way for Buyers and Sellers to meet in away that is better for Buyers, Sellers, and the hosting Search Enginecompany. The present invention is based on the fact that many Buyersknow what they want but are afraid to disclose this information for fearthat it will be misused or manipulated. It is also based on the factthat Buyers value their time and appreciate help from Sellers locatingrelevant products and services. Finally, the present invention is basedon the fact that Buyers with more money to spend tend to value theirprivacy more, and that savvy Sellers are eager to serve them in a mannerthat protects their margins while building trust.

The present invention also provides a Persistent Search Engine thatcaptures the most valuable marketing information—unfulfilled Buyerdemand. Every Buyer has a dream job, car, vacation, relationship, and soon. The present invention captures this valuable information andsearches for it. If a match is found, relevant items are shown in aconcise graphical manner controlled by the Buyer. If no matches arefound, the Persistent Search Engine keeps looking while the Buyer doesother things. This persistent search can continue indefinitely until thedesired item is found. The Buyer can return to the Persistent SearchEngine at any time to see how the search is progressing, or can benotified when relevant results are found. This solves the “dauntingchallenge” described by Google—knowing exactly a person wants to searchfor.

The real benefits from the Persistent Search Engine are for Sellersbecause each persistent search is really a lead from a Buyer activelylooking for a product or service. These leads are much more valuablethan clicks on organic or sponsored links because persistent searchescontain the specific features disclosed by the Buyer in a privateenvironment. These leads take the guesswork out of Sellers locatinginterested Buyers. They also give Sellers enough detail to enablepersonalized offers to Buyers.

The present invention also gives Sellers new proactive tools. Thepersistent search that permits Buyers to find Sellers is completelybi-directional, so it also permits Sellers to locate Buyers. This uniqueprocess not only permits Sellers to find Buyer searches based on commoncriteria, but the persistent nature of the Seller search permits them toimmediately find Buyers when new searches are entered or old searchesare modified. With this unique new tool, Sellers are no longer dependenton Buyers locating them.

In addition, both Buyers and Sellers can search, either one-time orpersistently, on their own peer group to learn how others buying orselling the same products or services are performing. This permits bothBuyers and Sellers to make adjustments in order to reduce waste andincrease profitability. Each search result also has an imbedded secure,private messaging system that permits Buyers and Sellers to communicatedirectly. This saves time, protects identities, and establishes trustthat is needed for long-term benefit of both Buyers and Sellers.

Moreover, the present invention eliminates the need to collectirrelevant information and therefore requires fewer resources tooperate. It also introduces new revenue models and reduces thedependency on sponsored links and the resulting exposure to click fraud.

More specifically, the present invention provides a method forelectronically searching for an item by receiving a search requestcomprising a requested category and one or more requested attributes ofthe item and storing the search request in a search index based on therequested category and the requested attribute(s). The search indexincludes one or more categories and each category is defined by ataxonomy of attributes. The search index is then searched for anypreviously stored search requests that match the requested category andthe requested attribute(s), a result of the search is determined and asearch response that includes the result of the search is sent. Notethat this method can be implemented using a computer program embodied ona computer readable medium wherein the steps are performed by one ormore code segments.

In addition, the present invention provides an apparatus forelectronically searching for an item that includes a search index and asearch engine communicably coupled to the search index. The search indexincludes one or more categories defined by a taxonomy of attributes. Thesearch engine receives a search request comprising a requested categoryand one or more requested attributes of the item, stores the searchrequest in the search index based on the requested category and therequested attribute(s), searches the search index for any previouslystored search requests that match the requested category and therequested attribute(s), determines a result of the search and sends theresult of the search. The apparatus may also include a user interfacefor entering the search request and receiving the result of the search,a data storage communicably coupled to the search engine, a brand layercommunicably coupled to the search engine or a private messaging systemcommunicably coupled to the search engine.

The present invention also provides a system for electronicallysearching for an item that includes a network, one or more user devicescommunicably coupled to the network, a user interface communicablycoupled to the network, a search index and a search engine communicablycoupled to the user interface and the search index. The user interfaceis used to enter a search request that includes a requested category andone or more requested attributes of the item and receive a result of thesearch. Note that the user interface can be resident on the one or moreuser devices. The search index includes one or more categories definedby a taxonomy of attributes. The search engine receives the searchrequest, stores the search request in the search index based on therequested category and the requested attribute(s), searches the searchindex for any previously stored search requests that match the requestedcategory and the requested attribute(s), determines the result of thesearch and sends the result of the search. The system may also include adata storage communicably coupled to the search engine, a brand layercommunicably coupled to the search engine or a private messaging systemcommunicably coupled to the search engine.

The present invention is described in detail below with reference to theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and further advantages of the invention may be betterunderstood by referring to the following description in conjunction withthe accompanying drawings, in which:

FIG. 1 is a block diagram of typical search engine technologies inaccordance with the prior art;

FIG. 2 is an example of a user interface and search result in accordancewith the prior art;

FIG. 3 is a block diagram of a system for searching for an item inaccordance with one embodiment of the present invention;

FIG. 4 is a block diagram of a system for searching for an item inaccordance with another embodiment of the present invention;

FIG. 5 is a flow chart of a method for searching for an item inaccordance with one embodiment of the present invention;

FIG. 6 is a block diagram of an Event Manager in accordance with oneembodiment of the present invention;

FIG. 7 is a typical process flow of one embodiment of the presentinvention;

FIGS. 8A, 8B and 8C are flow charts of process flow in accordance withone embodiment of the present invention;

FIG. 9 shows a screen used to Register as a Buyer or Seller, or Sign Inusing a Username and Password in accordance with one embodiment of thepresent invention;

FIG. 10 shows a screen used to register both Buyers and Sellers inaccordance with one embodiment of the present invention;

FIG. 11 is a screen showing an example of current persistent searches,along with a graphical relevance percent in accordance with oneembodiment of the present invention;

FIG. 12 is a screen shown when a persistent search is Deleted inaccordance with one embodiment of the present invention;

FIG. 13 is a screen listing the Categories grouped for easy review andselection in accordance with one embodiment of the present invention;

FIG. 14 is a screen used to create a new persistent search to findSellers in accordance with one embodiment of the present invention;

FIG. 15 is a screen used to create a new persistent search to findBuyers in accordance with one embodiment of the present invention;

FIG. 16 is a screen showing the Persistent Search Engine results for aBuyer looking for Sellers in accordance with one embodiment of thepresent invention;

FIG. 17 shows the Relevance Details of the selected search item inaccordance with one embodiment of the present invention;

FIG. 18 is a printer-friendly format of FIG. 17 in accordance with oneembodiment of the present invention;

FIG. 19 is a screen showing search preferences for the current user inaccordance with one embodiment of the present invention;

FIG. 20 is a screen showing a Privacy Policy in accordance with oneembodiment of the present invention;

FIG. 21 is a screen showing the Privacy Policy in more detail inaccordance with one embodiment of the present invention;

FIG. 22 is a block diagram showing another way that information flows toand from Buyers and Sellers in accordance with one embodiment of thepresent invention;

FIG. 23 is a flow chart showing one method to calculate the relativeimportance of any question and Answer pair in accordance with oneembodiment of the present invention;

FIG. 24 is a diagram illustrating a relevancy score calculation based ondistance in accordance with one embodiment of the present invention;

FIG. 25 illustrates the use of geometric distance calculation to score asearch in accordance with one embodiment of the present invention;

FIG. 26 illustrates the use of a genetic calculation to score a searchin accordance with one embodiment of the present invention;

FIG. 27 is a database design in accordance with one embodiment of thepresent invention;

FIG. 28 is a modeling tool that accepts a promotion criteria and budgetfor unsolicited offers (revenue model #8) in accordance with oneembodiment of the present invention;

FIG. 29 is a flow chart illustrating accepting a replay criteria (searchand time period) and then “replaying the tape” of buyer searches againstseller searches to find buyers, the latter of which can be modified tosimulate different results in accordance with one embodiment of thepresent invention;

FIG. 30 is a flow chart illustrating a simulation to repeat looking foroptimal or pre-stated results;

FIGS. 31-32 are examples of screen displays for a cell phone inaccordance with one embodiment of the present invention; and

FIG. 33 are examples of screen displays for an iPod in accordance withone embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

While the making and using of various embodiments of the presentinvention are discussed in detail below, it should be appreciated thatthe present invention provides many applicable inventive concepts thatcan be embodied in a wide variety of specific contexts. The specificembodiments discussed herein are merely illustrative of specific ways tomake and use the invention and do not delimit the scope of theinvention. The discussion herein relates primarily to Internet relatedapplications, but it will be understood that the concepts of the presentinvention are applicable to any interconnected database.

The present invention provides a system, method and apparatus forelectronically searching for an item that provides relevant searchresults, persistent searching and protects the privacy of its users. Forexample, the present invention reduces:

-   -   Dependency that Search Engine companies have on advertising        revenue. In doing so, this will also reduce click fraud. This        will enable Search Engine companies to earn more revenue by        providing more value to Sellers.    -   The need to store billions of irrelevant Web pages. This will        enable Search Engine companies to spend less on the cost of        collecting and managing information that has little or no value.    -   The need to collect personal information from Buyers and        possibly even Sellers. Not collecting personal information        builds trust because it reduces or eliminates the chance that it        will be disclosed to the wrong party or abused in any way.    -   The time required to find the desired item. This does much more        than make the search process easier for the Buyer. It is well        known that a Seller must save a Buyer either time or money.        Reducing the time to find the right product or service permits        Sellers to charge a premium price. This protects Seller margins.    -   The need to continue searching at a linked Website. This again        benefits both the Buyer by saving them time and the Seller by        protecting their margins.    -   The need for manipulating search results. This permits Buyers to        find products and services based on Buyer needs without        interference or comment from any other party.    -   Cluttered, irrelevant results. This permits Buyers to quickly        assess search results that are ranked by their own relevancy.

Moreover, the present invention increases:

-   -   Relevance without more and more complex algorithms. This        benefits all parties because Buyers and Sellers can find each        other based on common interests in a clear and concise manner.    -   Marketing information for advertisers, such as capturing “close        hit” data from partial interest, and “lost sales” data from a        Buyer that decided to continue with another Seller. This permits        Sellers to learn from mistakes and position their products and        services in a more efficient manner, even when the desired        results are not achieved.    -   Tools so Sellers can be more pro-active and not just wait for        Buyers. This permits Sellers to take the initiative in locating        Buyers in a proactive manner that does not violate the privacy        of either party.    -   Tools to get product and service information directly from        Seller legacy systems instead of having to “scrape” it from        Seller Websites.    -   Knowing in advance what Buyers and Sellers want.

Moreover, the present invention makes it extremely easy for a Buyer tospecify what they are looking for anywhere, anytime, and they controlthe final part of the searching and shopping process.

The present invention provides a way for Buyers and Sellers to meet in away that is better for Buyers, Sellers, and the hosting Search Enginecompany. The present invention is based on the fact that many Buyersknow what they want but are afraid to disclose this information for fearthat it will be misused or manipulated. It is also based on the factthat Buyers value their time and appreciate help from Sellers locatingrelevant products and services. Finally, the present invention is basedon the fact that Buyers with more money to spend tend to value theirprivacy more, and that savvy Sellers are eager to serve them in a mannerthat protects their margins while building trust.

The present invention also provides a Persistent Search Engine thatcaptures the most valuable marketing information—unfulfilled Buyerdemand. Every Buyer has a dream job, car, vacation, relationship, and soon. The present invention captures this valuable information andsearches for it. If a match is found, relevant items are shown in aconcise graphical manner controlled by the Buyer. If no matches arefound, the Persistent Search Engine keeps looking while the Buyer doesother things. This persistent search can continue indefinitely until thedesired item is found. The Buyer can return to the Persistent SearchEngine at any time to see how the search is progressing, or can benotified when relevant results are found. This solves the “dauntingchallenge” described by Google—knowing exactly a person wants to searchfor.

The real benefits from the Persistent Search Engine are for Sellersbecause each persistent search is really a lead from a Buyer activelylooking for a product or service. These leads are much more valuablethan clicks on organic or sponsored links because persistent searchescontain the specific features disclosed by the Buyer in a privateenvironment. These leads take the guesswork out of Sellers locatinginterested Buyers. They also give Sellers enough detail to enablepersonalized offers to Buyers.

The present invention also gives Sellers new proactive tools. Thepersistent search that permits Buyers to find Sellers is completelybi-directional, so it also permits Sellers to locate Buyers. This uniqueprocess not only permits Sellers to find Buyer searches based on commoncriteria, but the persistent nature of the Seller search permits them toimmediately find Buyers when new searches are entered or old searchesare modified. With this unique new tool, Sellers are no longer dependenton Buyers locating them.

In addition, both Buyers and Sellers can search, either one-time orpersistently, on their own peer group to learn how others buying orselling the same products or services are performing. This permits bothBuyers and Sellers to make adjustments in order to reduce waste andincrease profitability. Each search result also has an imbedded secure,private messaging system that permits Buyers and Sellers to communicatedirectly. This saves time, protects identities, and establishes trustthat is needed for long-term benefit of both Buyers and Sellers.

Moreover, the present invention eliminates the need to collectirrelevant information and therefore requires fewer resources tooperate. It also introduces new revenue models and reduces thedependency on sponsored links and the resulting exposure to click fraud.

Now referring to FIG. 3, a block diagram of a system 400 for searchingfor an item in accordance with one embodiment of the present inventionis shown. The system 400 includes three layers: a presentation layer402, a persistence layer 404 and a brand layer 406. The persistencelayer 404 can be used alone or in combination with the presentationlayer 402 and/or the brand layer 406. In other words, the persistencelayer 404 is added to any Buyer or Seller 408 search and may be accessedon one of three ways:

-   -   1. With a Presentation Layer 402 to enable discrete searches by        Buyers or Sellers 408 with their preferred device, such as PC,        laptop, cell phone, PDA, or iPod. This is a stand-alone        configuration where Buyers and Sellers 408 operate in a        fully-functional and targeted manner.    -   2. With a Brand Layer 406 to enable bulk searches via XML or EDI        by Buyers or Sellers 408 though legacy or similar systems 410        (Brand A), 412 (Brand B) and/or 414 (Brand C). This is an        enterprise configuration that takes adds persistence to one or        more established brands.    -   3. A combination of both discrete searches and bulk searches.

The Persistent Search Engine 416 is a unique type of “middleware”running on one or more servers. It only contains information importantto and specified by Buyers and Sellers 408. At the present time, in asupply-driven economy, there are more products and services than thereare Buyers. A visit to any department store or Web merchant makes thisevident.

As such, Seller information may be linked to the Search Index 418 inbulk through the Brand Layer 406 using an XML or EDI interface to aLegacy Systems 410, 412 and/or 414. Bulk Buyer information may also belinked in the same manner. In addition, discrete Buyer or Seller 408information may also be loaded directly into the Persistent SearchEngine 416 by the Presentation Layer 402 using any Web-enabled device.

As a result, the present invention provides an apparatus 404 forelectronically searching for an item that includes a search index 418and a search engine 416 communicably coupled to the search index 418.The search index 418 includes one or more categories defined by ataxonomy of attributes. The search engine 416 receives a search requestcomprising a requested category and one or more requested attributes ofthe item, stores the search request in the search index 418 based on therequested category and the requested attribute(s), searches the searchindex 418 for any previously stored search requests that match therequested category and the requested attribute(s), determines a resultof the search and sends the result of the search. The apparatus 404 mayalso include a user interface (presentation layer 402) for entering thesearch request and receiving the result of the search, a data storage420 communicably coupled to the search engine 416, a brand layer 406communicably coupled to the search engine 416 or a private messagingsystem 422 communicably coupled to the search engine 416. Note that thesearch index 418 is bi-directional between a buyer and a seller 424, thebuyer and another buyer 426, the seller and the buyer 428, or the sellerand another seller 430.

As shown in FIG. 4, the present invention also provides a system 500 forelectronically searching for an item that includes a network 502, one ormore user devices 504 communicably coupled to the network 502, a userinterface 506 communicably coupled to the network 502, a search index418 and a search engine 416 communicably coupled to the user interface506 and the search index 418. The user interface 506 is used to enter asearch request that includes a requested category and one or morerequested attributes of the item and receive a result of the search.Note that the user interface 506 can be resident on the one or more userdevices 504. The search index 418 includes one or more categoriesdefined by a taxonomy of attributes. The search engine 416 receives thesearch request, stores the search request in the search index 418 basedon the requested category and the requested attribute(s), searches thesearch index 418 for any previously stored search requests that matchthe requested category and the requested attribute(s), determines theresult of the search and sends the result of the search. The system 500may also include a data storage 420 communicably coupled to the searchengine 416, a brand layer interface 508 communicably coupled to thesearch engine 416 or a private messaging system 422 communicably coupledto the search engine 416. The search index is bi-directional between abuyer and a seller, the buyer and another buyer, the seller and thebuyer, or the seller and another seller.

Now referring to FIG. 5, a method 600 for electronically searching foran item is shown. The item may include a product, a service, a topic, aclassified-type advertisement, a personal-type advertisement or acombination thereof. A search request is received in block 602 andstored in a search index in block 604. The search request can be createdor initiated from a presentation layer, a persistence layer, a brandlayer or a combination thereof. The search request can be submitted by abuyer, a seller, a buyer/seller, a “window shopper”, a researcher, aninterested user or a combination thereof. The search request includes arequested category and one or more requested attributes of the item.Each attribute can be defined by a question and one or more answers tothe question, price, comments, feedback, etc. For example, it ispossible to have a search just on price (“I am looking for any car over$100,000”). The search request may also include a price, a price range,a description, one or more comments, one or more keywords, a minimumfeedback score for a user associated with any found stored searchrequest or a combination thereof. The search request is stored based onthe requested category and the requested attribute(s). The searchrequest may include: an item posted for advertisement, exchange, lease,sale, trade or transfer by a user; an item sought by a user foradvertisement, exchange, lease, sale, trade or transfer; informationposted about an item provided by a user; information about an itemsought by a user; a search for posted items that satisfy one or morecriteria; a search for sought items that satisfy one or more criteria; asearch for sought attributes; a search for sought information; a bulksearch; a search for close hits that satisfy one or more criteria; asearch for lost sales that satisfy one or more criteria; or acombination thereof.

The search index includes one or more categories and each category isdefined by a taxonomy of attributes. The taxonomy can differ based on alanguage, a culture or a region associated with the search request.Moreover, the search index is capable of providing matches regardless ofthe language, the culture or the region associated with the searchrequest. The search index is then searched for any previously storedsearch requests that match the requested category and the requestedattribute(s) in block 606, a result of the search is determined in block608 and a search response that includes the result of the search is sentin block 610. Each stored search request may include: an item posted foradvertisement, exchange, lease, sale, trade or transfer by a user; anitem sought by a user for advertisement, exchange, lease, sale, trade ortransfer; information posted about an item provided by a user; orinformation about an item sought by a user. The stored search requestsmay match the requested category and the requested attribute(s)whenever: the attributes of the stored search requests are equal to orexceed the requested attributes; the attributes of the stored searchrequests are substantially similar to the requested attributes; theattributes of the stored search requests are within a range of therequested attributes; or a relevancy score for the stored searchrequests is not satisfied. The search response can be sent to a userspecified device (e.g., a computer, a laptop, a handheld computer, ane-mail address, a personal data assistant, a telephone, a mobiletelephone, a portable media player, a portable communications device, afacsimile device, a Web-enabled device or a combination thereof, etc.).

Other steps may include: creating the search request by selecting therequested category from the one or more categories and selecting therequested attributes from the taxonomy of attributes for the requestedcategory; storing the price, the price range, the description, thecomments, the keywords, the minimum feedback score or the combinationthereof in the search index or in a data storage; updating the searchindex whenever a stored search request is added, changed or deleted;authenticating the received search request; deleting a stored searchrequest; resubmitting a previously submitted search request; or linkinginformation contained in a legacy database to the search index (theinformation can be linked via an XML or EDI index, loaded into thesearch index, loaded and indexed into a data storage or a combinationthereof).

Another series of steps may include: detecting a trigger event; wheneverthe trigger event is detected, searching the search index for any storedsearch results that match the requested category and the requestedattributes, and determining a new result of the search; and whenever thenew result differs from the result, sending an updated search responsecomprising the new result of the search. The trigger event can be anewly received search request, a change in the search request, aspecified time period, receipt of an update request, a change to thesearch index that would change the result of the search, a deletion of astored search request or a combination thereof.

The stored search request typically does not contain any personalinformation or only contains personal information added by the user. Forexample, the present invention can remove any personal information fromthe received search request before the received search request is storedin the search index.

As will be described in more detail below, the present invention maydetermine a relevancy score for each found stored search request, whichcan be displayed graphically. The determination of the relevancy scorecan be based on one or more user preferences, a closeness of therequested attributes in the search request to the attributes of thestored search request, a distance between an item associated with astored search request and a location of the user, a user specifiedbudget or a combination thereof. As illustrated in FIG. 23, thedetermination of the relevancy score may include a sum of relevancyscores for each requested attribute in the search request divided by thenumber of requested attributes in the search request, wherein therelevancy score for each requested attribute comprises a first valuewhenever the requested attribute is not specified in the stored searchrequest, a second value whenever the requested attribute matches theattribute of the stored search request and the requested attribute isrequired, a third value whenever the requested attribute that matchesthe attribute of the stored search request and the requested attributeis not required, a fourth value whenever the requested attribute thatdoes not match the attribute of the stored search request and therequested attribute is required, and a fifth value whenever therequested attribute does not match the attribute of the stored searchrequest and the requested attribute is not required. The relevancy scorecan be provided to the user associated with the stored search request,another interested user or a combination thereof.

The present invention may also include receiving one or more preferencesassociated with a user or the search request. The one or morepreferences may include an urgency, a results per screen, an minimumrequired relevancy limit, a minimum required rating associated with thestored search request, one or more user devices that are to be used forcommunications, one or more messaging limits or a combination thereof.

In addition, the present invention may send a notification to a userwhenever: the requested attributes of a received search request matchesa stored search request associated with the user; a received searchrequest is changed that previously matched the stored search requestassociated with the user; an item associated with a stored searchrequest is located within a specified distance from a location of theuser; the result of the search request by the user has changed; theresult of the search request by the user has not changed or a relevancyscore for the stored search requests is not satisfied. The notificationmay include a request to return to the stored search request or theresult of the search, a link to return to the stored search request orthe result of the search, a description of a reason for thenotification, a message, a new search request or a combination thereof.

Moreover, the present invention may provide a messaging system between auser that submitted the search request and each user associated with thestored search requests that matched the requested attributes. Themessages within the messaging system are private between the user thatsubmitted the search request and each user associated with the storedsearch requests that matched the requested attributes and cannot beaccessed by third parties. Furthermore, the messages within themessaging system do not contain any personal information about the userthat submitted the search request and each user associated with thestored search requests that matched the requested attributes unless suchpersonal information is added by one of the users. The messages withinthe messaging system do not have to be tied to a mail server or ane-mail address, but are typically logged and tied to the search request.The user that submitted the search request and each user associated withthe stored search requests that matched the requested attributes canspecify a limit on the number of messages that another user can send tothem. The user can add an attachment or additional content to themessages within the messaging system if the attachment satisfies one ormore criteria. The user can accept unsolicited offers, unsolicitedmessages, questionnaires, advertisements or a combination thereof ifsuch offers, messages, questionnaires or advertisements satisfy one ormore criteria.

The present invention may also receive feedback or comments regarding auser, a stored search request or a combination thereof, and associatethe feedback or comments with the user or the stored search request orthe combination thereof.

The above described steps can be repeated until a specified time periodhas elapsed, a specified number of searches are performed, the searchrequest is changed, deleted or terminated by the user, the searchrequest is changed, deleted or terminated by a system, the searchrequest is replaced or a combination thereof. In addition, the step ofsearching the search index is halted after a specified number of matcheshave been found. Moreover, the above described steps (e.g., storing thesearch request, searching the search index, determining the result ofthe search, sending the search response, etc.) can be performed at alevel of functionality associated with a user associated with thereceived search request.

Note that the methods, steps and processes described herein can beimplemented using a computer program embodied on a computer readablemedium wherein the steps are performed by one or more code segments.

The Persistent Search Engine 416 is driven by a collection ofBuyer/Seller Categories, such as computers, houses, jobs, vacations, andso on. Each Category is driven by an associated Taxonomy, which is acollection of Questions and Answers that define the features and optionsgot the products or services of that category. The following table showsa small part of the Taxonomy for buying and selling cars:

Question Answers Make Ford, Buick, Chrysler Model If Ford: Aerostar,Aspire, Bronco, Bronco . . . If Buick: Century, Electra, Lacrosse,LeSabre . . . If Chrysler: 300, 300C, 300M, Cirrus, Concorde . . . ColorWhite, black, grey, blue, red, green, yellow . . . Doors 2, 3, 4, 5 Year1990, 1991, 1992, 1993, 1994, 1995, 1996 . . . Options Power steering,power windows, side airbags . . .

Using Taxonomy Questions and Answers like these, it is possible todescribe virtually any car, whether it's currently made or not. Theseare entered by the Buyer and stored in the Search Index. Additionalinformation, such as price and comments, can be stored in the SearchIndex or Data Storage. This is a highly efficient way to store Buyerinformation because there is no waste—only unfulfilled Buyer demand isrequired, and the needs of millions of Buyers can fit into a singleserver.

Sellers use the same Category and Taxonomy to find Buyers by matchingcommon Answers to the same Questions. This bi-directional “dual searchengine” enables several unique capabilities:

-   -   A new type of search engine that locates high-propensity Buyers,        along with the features that are important to them.    -   The ability to position a product or service in a manner that is        relevant to the Buyer. This personalization is made easy because        the Buyer has described the item based on desired features. This        “mass-customization” protects Seller margins while increasing        the relevance to Buyers.    -   Requested products and services do not have to exist. In a        demand-driven, mass-customized economy, Sellers learn what        Buyers want and benefit by knowing new feature combinations that        have yet to be commercialized. This is much more cost-effective        than traditional market research and prototype testing.    -   Highly flexible, virtually unlimited demand-driven searching.        For example, a Seller can search for Buyers looking for 20″        monitors and then offer them a 24″ monitor using new technology        for the same price.    -   Precise definitions. Keywords are arbitrary, can be misspelled,        and are different from culture to culture and language to        language. In addition, Taxonomy Questions and Answers can be        selected using a pointing device, such as a remote control, or        can be selected by using the numbers on, say, a cell phone. This        is important as more Web-enabled devices become mobile and        keyboards are eliminated. Taxonomy Questions can have Answers        entered on cell phones, PDAs, iPods, and so on.    -   Computer-aided learning. For Buyers, Taxonomy Questions and        Answers provide education about features that they may not have        known.    -   Differentiation. This permits Sellers to sell on features and        not price, thus protecting margins. If, for example, a Seller's        product has a unique feature, Buyers will quickly learn about it        and know where to get it. Sellers not offering this feature will        ranked lower in relevancy.    -   Quantified lost sales. Sellers not having a particular feature        will have a lower relevancy but will learn from what worked for        a competitive Seller.    -   The same individual can be both a Buyer and Seller at the same        time. For example, a person could be using the Persistent Search        Engine to sell an old car and buy a new car at the same time.    -   Peer marketing intelligence. Buyers can learn from other Buyers        looking for similar products and services. Because of the        bi-directional nature of the present invention, Sellers can also        learn from other Sellers.

All of these Buyer and Seller searches are stored in Search Index 416and/or Data Storage 420. The process of storing them and locating themlater, either as the Buyer or Seller, is how all searches in thePersistent Search Engine 416 are made persistent. A new search, a changeto an existing search, or an old search being terminated all update theSearch Index immediately and trigger the Events Manager 700 as shown inFIG. 6.

FIG. 6 shows one preferred embodiment of how information flows fromBuyer 702 to Seller 704. Part of the Persistent Search Engine 416includes an Event Manager 700 that manages how information isdistributed. For example, Buyer Leads can be sent to a Seller 704 bye-mail 716 and/or cell phone 718 and/or XML 722. The design of thePersistent Search Engine 416 is mirrored and is referred as a “dualsearch engine.” As such, FIG. 6 also describes how information flowsfrom Seller 704 to Buyer 702, Seller 704 to Seller 704, and Buyer 702 toBuyer 702. Examples may include:

-   -   A drop in price can notify interested Buyers 702 and/or other        interested competitive Sellers 704.    -   A Buyer search that terminates can notify a Seller 704 with a        similar product or service that the Buyer 702 may need help        finding a similar product.    -   A Buyer 702 terminating a search because a product was purchased        can quantify lost sales for similar Sellers 704. This also gives        Sellers 704 one more opportunity to cross or up-sell the Buyer        702. For example, the Seller 704 may not sell the car but may be        able to service the car.    -   Buyers 702 can watch from and learn from similar Buyers 702.        Increasing Buyer peer pressure increases prices, while        decreasing peer pressure increases Buyer power.    -   In exactly the same manner, Seller peer groups can educate        Sellers 704 about how to adjust their products, services, and        prices to maximize profitability.        Using the Event Manager 700, Buyers 702 are able to find leads        706, search changes 708, conduct research 710, send private        messages 712 and monitor/observe behavior 714. The Events Manger        700 can notify Sellers 704 of changes or other information via        e-mail 716, cell phone 718, private messages 720, RSS 722 and        XML 724.

The efficient use of Search index 418 in the Persistent Search Engine416 enables a highly-efficient process that eliminates the need tocollect, store, and index data from billions of Web pages. According topublished reports, Google has over 150,000 servers processing 200million searches daily. This means that each server processes an averageof just one search request per minute. The Persistent Search Engine 416can process between 50 and 500 search request per second. The differenceis that current search engine technologies manage content from billionsof irrelevant Web pages in disk files, while the Persistent SearchEngine 416 manages millions of relevant search requests in amemory-resident index.

Another component of the Persistent Search Engine 416 is the PrivateMessaging System 422. Every persistent search has an embedded facilitythat enables direct, private communication with the person who initiatedthe search. This enables several unique capabilities:

-   -   Messages are search specific, making them relevant and focused.    -   Messages cannot be accessed by bulk e-mailers.    -   Messages operate fully within the Persistent Search Engine 416        and are not tied to any mail server or e-mail addresses. Any        pictures, attachments, or links must be accepted and approved by        the present invention before they are sent. As such, people        receiving messages can be confident that they cannot carry        viruses or other damaging payloads.    -   Messages assure anonymity because they only include personal        information if the sender intentionally discloses it in the text        of the message.    -   Each Buyer or Seller search has a log of all associated        messages. This makes the search process easier to manage because        related messages are shown with the search details.    -   A Buyer or Seller can specify the number of consecutive messages        that any individual can send for any given persistent search. If        set to 2, then two consecutive messages can be sent by a sender        before the messaging feature is automatically disabled for this        search result. This counter is reset when the other party        replies to a message. If set to 1, then a sender has just one        chance to get a response. This eliminates multiple messages that        are of no interest to the receiver, and it ensures that the        sender keeps the messages relevant. Any receiver of messages can        use this feature, so it protects both Buyers and Sellers.

Now referring to FIG. 7, a typical process flow 800 of one embodiment ofthe present invention is shown. The process 800 begins when a user goesto the Register/Sign In screen 802 (FIG. 9) where the user eitherregisters as a Buyer and/or Seller in screen 804 or Signs In. Oncecomplete, the user goes to the Search Summary screen 806 (FIG. 12). Theuser can then select a category for a new search in Category screen 808(FIG. 14). From there or from the Search Summary screen 806, the usercan add/edit a search for a Seller/Buyer with screen 810 a (FIG. 15),810 b (FIG. 16). From there or from the Search Summary screen 806, theuser can go to the Search Relevance screen 812 (FIG. 17). From there,the user can go to a Detailed Relevance screen 814 (FIG. 19) to examinedetails about the stored search request. From there, the user cancommunicate with the Buyer/Seller using the Private Messaging system422. It should be noted that once a person has registered or signed-on,they may use navigational links 816-828 to jump directly from one partof the present invention to another (e.g., Preferences 816 (FIG. 21),Help 818, Privacy 820 (FIG. 22), Terms 822, About 824, FAQ 826, Contact828, etc.). For example, a Buyer looking at Detailed Relevance 814 canlink to Preferences 816 to increase the number of search results perscreen and then can link directly to Category 808 to start a new search.

Referring now to FIGS. 8A, 8B and 8C, flow charts of a process flow inaccordance with one embodiment of the present invention are shown. FIG.8A shows the Registration/Sign In flow. FIG. 8B shows the initial flowonce Registration or Sign In is complete. A Summary of each persistentsearch is shown. Clicking on a persistent search takes the user to FIG.8C and shows the relevance for all search results. Other options includelinks for selecting a Category, starting a new search to Find Buyers orFind Sellers, changing user Preferences, getting Help, or Sign out.These links are common for most screens to facilitate easy movementthroughout the Persistent Search Engine. As explained in FIG. 8B, whenan existing search is selected in FIG. 11, or when a new search iscreated in FIG. 12 or FIG. 13, the process flow continues as shown inFIG. 8C. The user can review the Search Relevancy in summary, in detail,and can send the person associated with the search details.Alternatively, the user can return to the Search Summary or can edit thecurrent persistent search.

The process begins at 900 and registration/sign in is performed in block902. If the sign in is authenticated or the registration information isaccepted in block 904, a search summary is shown in block 906. If acategory is clicked, as determined in decision block 908, a seller editflag is set in block 910 and a category is selected in block 912. If,however, a category is not clicked, as determined in decision block 908,and a new search is clicked, as determined in decision block 914, and acategory is not selected, as determined in decision block 916, acategory is selected in block 912. If however, a category is selected,as determined in decision block 916, or a category is selected in block912, and a buyer search is selected, as determined in decision block918, buyer search information is accepted in block 920. If, however, aseller search is selected, as determined in decision block 918, sellersearch information is accepted in block 922. If a new search is notselected, as determined in decision block 914, or the buyer searchinformation is accepted in block 920, or the seller search informationis accepted in block 922, search relevance is shown in block 924.Thereafter, if home is clicked, as determined in decision block 926, theprocess returns to block 906 where the search summary is shown. If editis clicked, as determined in decision block 928, the process returns todecision block 918 where the type of search (buyer or seller) isdetermined. If home is not clicked, as determined in decision block 916,and edit is not clicked, as determined in decision block 918, therelevance details are shown in block 930. Thereafter, if home isclicked, as determined in decision block 932, the process returns toblock 906 where the search summary is shown. If relevance is clicked, asdetermined in decision block 934, the process returns to block 924 wherethe search relevance is shown. If edit is clicked, as determined indecision block 936, the process returns to decision block 918 where thetype of search (buyer or seller) is determined. If home is not clicked,as determined in decision block 932, and relevance is not clicked, asdetermined in decision block 934, and edit is not clicked, as determinedin decision block 938, private messages can be accepted or sent in block938. Thereafter, the process returns to block 930 where relevancedetails are shown.

Now referring to FIG. 9, a screen 802 used to Register as a Buyer orSeller, or Sign In using a Username and Password in accordance with oneembodiment of the present invention is shown. The user can register as aBuyer by clicking “Register Now” 1000 or as a Seller by clicking“Register Now” 1002. If the user has already registered, the user canSign In by entering his/her Username 1004 and Password 1006. Other SignIn embodiments include biometrics, personalized encrypted identificationdevices, or other authentication methods. Guest access 1008 may permitan unregistered person limited access to the present invention, such asa search to find a Buyer of Seller without access to Relevance Details,Private Messaging, or making the search persistent.

Referring to FIG. 10, a screen 804 used to register both Buyers andSellers in accordance with one embodiment of the present invention isshown. The “dual search engine” nature of the present invention meansthat a Buyer can search for a Seller, any Seller can search for a Buyer,and any user can be both a Buyer and Seller at the same time. TheRegistration screen 804 accepts the information 1102 required to be aBuyer, which is intentionally minimal (e.g., Username 1106 (required),Password 1108 (required), Password hint 1110 (required), zip code 1112,code 1114 shown in block 1116, etc.). If the user wants to also be aSeller, he or she can optionally enter additional personal information1104 (e.g., name 1118, address 1120, e-mail address 1122, website 1124,terms and conditions 1126, etc.). This is optional because for certainCategories, such as oil and gas brokering, both Buyer and Seller want toremain anonymous. Additional information could be entered but is notshown. Once the information is entered, the user clicks on Register 1128to complete the process.

Now referring to FIG. 11, a screen 806 showing an example of currentpersistent searches, along with a graphical relevance percent inaccordance with one embodiment of the present invention is shown. Screen806 lists current persistent searches, along with a graphical relevancepercent for each search. There are two types of persistent searchesshown: searches to find Sellers 1200 and searches to find Buyers 1202.Each persistent search result includes Category 1204, My Description1206, Since 1208 (when the search was started), search result Relevance1210, Close Hits 1212, Really Close Hits 1214, unread Private Messages1216, and Delete button 1218. Relevance 1210 is the result of acalculation between what the Buyer and Seller are looking for and isdiscussed later. Relevance 1210 is displayed as a bar graph (poor, fair,good, very good and excellent) and a percentage. Close Hits 1212 is acounter is incremented for a search to find Sellers every time a Sellerlocates this search and sees it in Search Relevance 1210, and ReallyClose Hits 1214 is incremented every time a Seller sees it in RelevanceDetails 814. Likewise, Close Hits 1212 for a search to find Buyers isincremented every time a Buyer sees it in Search Relevance 1210, andReally Close Hits 1214 is incremented every time a Buyer sees it inRelevance Details 814.

Referring now to FIG. 12, a screen 1300 when a persistent search isDeleted (clicking on Delete button 1218 in FIG. 11) in accordance withone embodiment of the present invention is shown. It gives the user achance to verify that the search needs to be Deleted by requiring theuser to click on “Delete this search” 1302. It also gives the user achance to Archive the search for later access by checking box 1304. Italso permits the user to specify reasons why the search request is beingdeleted (e.g., the desired item was found through this search 1306, thedesired item was found another way 1308, just wanted to stop the search1310, etc.). This helps other users quantify if they lost a sale.

Now referring to FIG. 13, a screen 808 listing the Categories groupedfor easy review and selection in accordance with one embodiment of thepresent invention is shown. When a Category 1400 is selected, it is madethe current Category, is shown the top of each screen, and thecorresponding Taxonomy is loaded for adding the next persistent search.The Categories 1400 are grouped into subject areas 1402 for easy reviewand selection. For example, the subject areas may include real estate,motor vehicles, employment, financial services, residential services,professional services, travel, vacation, computers, entertainment,dining, dating, hobbies, electronics, furniture, tools, homeimprovement, office supplies, household items, sporting goods, sportingevents, recreation, event tickets, a combination thereof or any otherdesirable subject area. The Categories within the real estate subjectarea may include houses, apartments, land, farms, commercial, insurance,finance or moving/storage. The Categories within the motor vehiclessubject area may include cars, trucks, recreational, repairs, insuranceor finance. The Categories within employment may include administrative,professional, education, healthcare, retail or manufacturing. TheCategories within financial services may include mortgages, loans,brokerage accounts, mutual funds, small business or bill pay. TheCategories within residential services may include plumber, electrician,lawn & garden, appliance repair, remodeling or cleaning. The Categorieswithin professional service may include attorneys, accountants orcomputer services.

Referring now to FIG. 14, a screen 810 a used to create a new persistentsearch to find Sellers in accordance with one embodiment of the presentinvention is shown. As shown, Description 1500, Price From 1502, PriceTo 1504, Zip Start In 1506, Prefer Results Within 1508, Exclude ResultsOutside 1510, Comments 1512, and Urgency 1514 are all common fields. Thefields in the middle are the Taxonomy Questions and Answers 1516. Notethat Taxonomy answers can be Nice to Have 1518 and Must Have 1520 thatare used to help calculate search result Relevancy. The presentembodiment has drop-down boxes and the user may select one Answer fordesired Questions, such as year built, and more than one Answer forother types of Questions, such as options available in a car. Answers toone Question may be dependant on Answers to other Questions. Forexample, a car Make of Ford configures the Answers to Model to thevarious Ford products, such as a Mustang. Other embodiments includeselecting the requested attributes one or more check boxes, one or moreradio buttons, one or more thumbnail pictures or videos, voicerecognition, a fuzzy logic algorithm, a neural network, other types ofpresentation methods that may educate and guide the user andcombinations thereof.

Note that the default Question name definitions can change from oneCategory to another. A car customer talks with a car dealer about price,whereas a job-seeker talks with an employer about salary. These are usedto make the present invention friendlier and more relevant:

Cars Employment Buyer Customer Job-seeker Seller Dealer Employer From/Tovalue Dollars SalaryBecause Taxonomy definitions, Questions, and Answers are defined atrun-time by the values stored for each Category, the same capability canbe used to make Taxonomies work with different cultures and languages.

Now referring to FIG. 15, a screen 810 b used to create a new persistentsearch to find Buyers in accordance with one embodiment of the presentinvention is shown. As shown, Description 1500, Price 1600, Zip Start In1506, Prefer Results Within 1508, Exclude Results Outside 1510, Comments1512, and Urgency 1514 are all common fields. The fields in the middleare the Taxonomy Questions and Answers 1516. Note that Taxonomy answerscan be Nice to Have 1518 and Must Have 1520 that are used to helpcalculate search result Relevancy. The present embodiment has drop-downboxes and the user may select one Answer for desired Questions, such asyear built, and more than one Answer for other types of Questions, suchas options available in a car. Answers to one Question may be dependanton Answers to other Questions. For example, a car Make of Fordconfigures the Answers to Model to the various Ford products, such as aMustang. Other embodiments include selecting the requested attributesone or more check boxes, one or more radio buttons, one or morethumbnail pictures or videos, voice recognition, a fuzzy logicalgorithm, a neural network, other types of presentation methods thatmay educate and guide the user and combinations thereof.

Referring now to FIG. 16, a screen 812 showing the Persistent SearchEngine results for a Buyer looking for Sellers in accordance with oneembodiment of the present invention is shown. Note that this can also befor Sellers looking for Buyers, for Buyers looking for other Buyers, andfor Sellers looking for other Sellers. For each Seller, the screen 812displays a Description 1700, Since 1702 (when the search was started),Price 1704, search result Relevance 1706, Private Messages 1708, TimesReplied 1710, and Delete button 1712. The Relevancy percent is based onthe Taxonomy Questions and Answers, Nice to Have, Must Have, Price,location, keywords in the Comments, and other search criteria. If theuser selects a search item, FIG. 17 appears next.

Now referring to FIG. 17, the Relevance Details screen 814 of theselected search item in accordance with one embodiment of the presentinvention is shown. This includes all Taxonomy Questions and Answers ofboth the Buyer 1800 and Seller 1802 and whether or not the attributesmatch 1804. Colors may be used to indicate Answers that matched or didnot match that were used to calculate the Relevancy percent. From thisscreen, the user can more forward or backward in the search results tolook at the Relevancy Details of the other search items in FIG. 16without leaving the current screen (buttons 1806). This screen also hasa list of private messages 1808 sent to and from the Seller, otherparty, as well as a place to enter a new message 1810 to send to thisSeller. The number of remaining messages 1812 is shown so that the useris encouraged to send relevant information. If no more messages can besent, then no message can be entered and a warning is shown. The usercan also click on Never Show Again 1814 to permanently remove thissearch result from Search Relevance. The user may also select the Printbutton 1816 if a hardcopy of this screen is required. FIG. 18 is aprinter-friendly format of FIG. 17 in accordance with one embodiment ofthe present invention. It is intended to be used as a permanent recordof the search and messages. For example, it can be taken to a car dealeras proof of the terms and conditions agreed to between the Buyer andSeller.

Referring now to FIG. 19, a screen 816 showing search preferences forthe current user in accordance with one embodiment of the presentinvention is shown. The search preferences can be selected and changedat any time to personalize persistent search results. Urgency 2000defines which persistent search results require special processing, andthis processing can include being e-mailed 2002 and/or sent to theuser's cell phone 2004. Note that this urgency definition 2000 can beoverridden by any specific search. Other preferences include the numberof Persistent Search Engine results 2006 to show on the Search Relevancescreen, which search results are to be ignored 2008, how the graphicrelevancy results are to be shown 2010, and how to filter out searchresults associated with Buyers and Sellers with low Star Ratings 2012.The user may also request that the Search Summary or other search resultbe e-mailed on a daily basis 2014. The user also indicates the number ofconsecutive messages that he or she will permit without replying 2016.This gives the user control over spam and other types of abuse. The usermay also specify how much his or her time is worth per hour 2018 forUnsolicited Offers and Questionnaires. Preferences are one way thatadditional functionality is added to the present invention. ThePreferences are saved by clicking on Save 2020.

Now referring to FIG. 20, a screen 820 showing a Privacy Policy inaccordance with one embodiment of the present invention is shown. Notethat the emphasis is on not collecting personal information. FIG. 21shows the Privacy Policy in more detail.

Referring now to FIG. 22, a block diagram 2300 showing another way thatinformation flows to and from Buyers 2302 and Sellers 2304 in accordancewith one embodiment of the present invention is shown. A persistentsearch by a Buyer 2302 to find Sellers 2304 is a primary process. Apersistent search for a Seller 2304 to find a Buyer 2302 is unique and apowerful new tool for eCommerce. In addition, a persistent search byBuyers 2302 to find and monitor similar Buyers 2306 provides importantinformation that helps Buyers 2302 make more informed decisions. Forexample, if there are many other Buyers 1306 looking for the sameproduct, a Buyer 2302 knows that their bargaining position is weakenedand he or she must act accordingly. If there are few other Buyers 2306looking, then a Buyer 2302 knows that their stronger bargainingposition. The same is true for Sellers 2304. If there are many Sellers2308 offering the same product, the Seller 2304 knows that theirbargaining position is weak and they can withdraw the sale or enternegotiations properly prepared. If there are few other Sellers 2308,then a Seller 2304 is in a much stronger position. Applied to onlineauctions, it is possible for a Seller 2304 to locate a Buyer 2302 for agood selling price without the need to have an auction and await theoutcome.

Now referring to FIG. 23, a flow chart 2400 showing one method tocalculate the relative importance of any question and Answer pair inaccordance with one embodiment of the present invention is shown. ThePersistent Search Engine does not permit manipulation of any searchresults because they are calculated entirely based on how well theTaxonomy Answers of a search match the existing Answers of existingsearches. The only way a Seller, for example, can improve its placementwith Buyers is to use the many tools provided by the present inventionto meet the unfulfilled demand of Buyers. Buyers or Sellers who providefalse Answers to Questions receive lower Five Star Ratings and arequickly filtered out of search results.

The method 2400 for determining the relative importance of any Questionand Answer pair (attribute) is repeated for each question in theTaxonomy in the search Category. The present embodiment ignoresunspecified attributes in the scoring by excluding them from theaverage. This is done to focus on Questions that have been answered. Ifattributes match and are Must Have, the score for this Answer is 100. Ifthey match and are Nice to Have, the score is 95. If they do not matchand are Must Have, the score is 0, otherwise 25 for Nice to Have. Theattribute scores are then average determine Relevancy percent. Partialmatch scoring would be possible by limiting the specific attributesunder consideration. For example looking for a car and financing couldbe included in the same search, but provided by different Sellers. Sincea bank isn't in the business of selling cars this would necessitate theability to ignore the attributes which are specific to car selection.

More specifically, if the Answer is blank, as determined in decisionblock 2402, 100 is added to the current sum in block 2404. If, however,the Answer is not blank, as determined in decision block 2402 and theAnswers are the same, as determined in decision block 2406, and theAnswer is Must Have, as determined in decision block 2408, 100 is addedto the current sum in block 2410. If, however, the Answer is not MustHave, as determined in decision block 2408, 95 is added to the currentsum in block 2412. If, however, the Answers are not the same, asdetermined in decision block 2406, and the Answer is Must Have, asdetermined in decision block 2114, 0 is added to the current sum inblock 2416. If, however, the Answer is not Must Have, as determined indecision block 2114, 25 is added to the current sum in block 2418. Ifthere is not another Answer, as determined in decision block 2420, afterthe proper amount has been added to the current sum in block 2404, 2410,2412, 2416 or 2418, the Relevance is calculated in block 2422. If,however, there is another Answer, as determined in decision block 2420,the process loops back to decision block 2402 and continues aspreviously described until all Answers evaluated.

In another embodiment, a third modifier to an attribute could be usedfor search elimination. “Absolute attributes” would eliminate a searchfrom consideration if that attribute's score is 0. A modification tothis scoring method is useful for adding a proximity filter to thescores, as shown in FIGS. 14 and 15. The Zip Code of the Buyer searchand Seller search are used to calculate the Distance between the twopoints. This is then used with FIG. 24 to calculate the score. Theradius of the inner circle 2504 is from Prefer Results Within 2500 andis given a score of 100. The radius of the outer circle 2506 is fromExclude Results Outside 2502 and Distances that exceed this are given ascore of 0. The score between the two circles is calculated from 100 to0 depending on the Distance from the center. The rules for calculatingcan be stored in Preferences for this user or Category. Another examplecould be cars that do not have the color of red are to be eliminatedfrom the results, and not just scored with a lower Relevance.

In another embodiment, Distance could be the major search factor. Forexample, a search for a car would exclude cars outside Exclude ResultsOutside, irrespective of the other Relevancy calculations. In anotherembodiment, the Zip Code of the Buyer and Seller are dynamically updatedbased on the location of, for example, a person's cell phone. A Buyercould, for example, be driving and be notified by the Event Manager bycell phone if he or she drives within Preferred Radius Within of adesired item. In another embodiment, a seven digit Zip Code can be usedfor more accurate Distance Calculations.

Another embodiment would be to use a geometric distance calculation toscore a search. The attributes are given coordinates on a graph(Cartesian, radial, or otherwise) with n-dimensions, the furthest anyattribute value can be away from other attribute values is 0.999999(effectively 1) on a given axis, as shown in FIG. 25 as a 2-dimensionalCartesian example. This means that taking the (1−attribute distance)*100will calculate the Relevance percent. This also allows for othergeometric plots to be use to represent different attribute types, suchas ranges. Attributes could be plotted by hand, using the currentpopulation, using a predefined function, or any combination. AbsoluteAttributes could be also added as a score multiplier. Partial matchscoring would be possible by limiting the number of dimensions underconsideration.

In another embodiment, fields are matched based upon a genecompatibility (see FIG. 26). A universally compatible gene would be usedto represent a “not specified” attribute. Must Have and Nice to Havewould be represented by a gene factor which would affect compatibility.Scoring could be based upon a male focused (the search being matched,the current users search) missed gene factor average, a weighted misshit ratio as in Attribute Scoring, or a combination thereof. AbsoluteAttributes could be also added as a score multiplier. Partial matchscoring would be possible by limiting the number of genes underconsideration. In another embodiment, Relevance calculation scores canbe stored in Preferences or Categories for this user. This permits anyuser more granular control over his or her search Relevancycalculations.

The database design of one embodiment of the present invention is shownin FIG. 27. In the searching process, fields are matched based uponmatches searchdesc.attribid and searchdesc.valueid. Note that valueidwould be sufficient because in the current embodiment, every value has aunique id.

Counters (“Five Star Ratings”) are kept on all Buyer and Selleractivities. This includes permitting Buyers to rate Sellers. The percentof satisfied Buyers that a Seller has helps other Buyers decide if theyshould trust the Seller. A global filter in Preferences can be adjustedin any specific search by having a Taxonomy Question and correspondingAnswers so that Sellers below a Buyer-defined threshold may beeliminated from the search results. In the same manner, a Buyer thatacts inappropriately, such as abusing the Unsolicited Offers andQuestionnaires revenue model, can be filtered out of Sellers searches tofind Buyers. This effectively eliminates Buyers that commit “clickfraud”, a significant problem with current keyword-driven searchtechnologies.

The present invention also provides various new revenue models. Currentkeyword search engine technologies must accept a command, search thecontent of billions of Web pages stored in Data Storage, prioritize theresults, and display them in a less than one second. A “persistent”search can last for minutes, hours, days, or even months. This enablesseveral unique revenue models because both Buyers and Sellers can learnmuch more over time. In the preferred embodiment, the following revenuemodels are typical:

-   -   1. Subscription fees can be charged to Sellers and, for some        Categories, Buyers for basic access to the Persistent Search        Engine. The unique nature of a search engine to find Buyers        enables this most basic revenue model.    -   2. Buyer Leads because each persistent Buyer search is really a        lead that contains what product or service features are        important. Higher click through rates are enabled because of        assured privacy, assured relevance, convenience, and        personalization possibilities. Higher revenue per lead is        enabled because some of the Categories are for major ticket        items, such as cars. Revenue per lead can be a flat amount or        tied to the value of the item. For example, a lead for a used        Camry might be worth $20 whereas a for a new Lexus might be        worth $100.    -   3. Priority Leads permits a Seller's persistent search to be        notified quickly when a new search result is found. This could        be by priority E-mail, Cell Phone, Private Messaging, RSS feed,        XML connection, as shown in FIG. 19. For example a car lead with        a high Relevance percent could be sold for $100 if immediately        forwarded by the Event Manager, and $50 for regular processing        that might have a 4 hour delay.    -   4. Broadcast Buyer Leads to Sellers that may or may not be using        the Persistent Search Engine. For example, a Buyer search for a        certain car would be broadcast to all car dealers in a certain        trade area. If the car dealer uses the Persistent Search Engine,        a link could take the dealer directly to the Relevance Details        screen. If the car dealer does not use the Persistent Search        Engine, details of the Persistent Search Engine can be included        in the lead. These Broadcast Buyer Leads represent “lost sales”        reports for all recipients of the broadcast if they do not act        upon these leads.    -   5. Peer Group Marketing Intelligence fees for Buyers searching        for similar Buyers and Sellers searching for similar Sellers.        For example, a person selling their home would gain valuable        marketing intelligence knowing what other similar homes are on        the market. In addition, a person buying a home would gain        valuable marketing intelligence knowing how many other people        are trying to buy a similar home. Knowledge is power, and these        tools represent another revenue model for the Persistent Search        Engine.    -   6. Changes to Persistent Searches, such a price change or a        search being terminated. For example, a change to the price of a        home being offered by a Seller can notify Buyers looking for        similar homes, as well as Sellers selling similar homes. A fee        can be charged for this information.    -   7. Quantifying the Level of Interest that a Buyer or Sellers        has. This behavior can be measured with a combination of        Persistent Search Engine information, including Close Hits,        Really Close Hits, the number of times a person looked at a        search result, and the time they have spent looking at a search        result. The present invention provides value even when a search        is not completed, and a fee can be charged for this information.    -   8. Unsolicited Offer and Questionnaire fees permit Sellers to        contact Buyers with products or services that are not Relevant.        The Persistent Search Engine protects Buyers by only returning        Relevant offers, and Sellers that abuse this can be eliminated        from search results by unfavorable Five Star Ratings. However,        there needs to be a way to for Sellers to educate Buyers about        products and services that they may be unaware of The Persistent        Search Engine permits this by giving Buyers the option to        specify how much their time is worth and then have Sellers buy        this time so that unsolicited offers may be considered and then        commented on. For example, a Buyer may be searching for a Ford        product. Chrysler could offer to purchase 10 minutes of the        Buyer's time for $10 so that Chrysler can educate the Buyer of a        competitive product. Payment could be by check, airline points,        gift certificates, or any other method that does not violate the        privacy of the Buyer. This represents a highly cost-efficient        way that, for example, can Chrysler educate a Buyer just before        the purchase of a competitive product. At worst, Chrysler gets        is answers to question about why a competitive product is being        purchased, something that is currently very difficult to        capture. At best, Chrysler salvages a sale. This represents the        cheapest way to find the most valuable person—a real buyer just        before he or she is lost to a competitor. This is a true        breakthrough for reducing customer acquisition costs. Included        is a modeling tool to ensure the most efficient use of promotion        budgets.    -   9. Messaging fees can be charged to the Seller and possibly        Buyer. This enables, for example, leads to be broadcast with        detailed information to any party and only charging that party        if they act upon a broadcast lead by sending a Message.    -   10. Quantified Lost Sales can be sold in real time to educate        Sellers, both those that bought a lead and those just observing        Buyer Behavior. In the brick-and-mortar world, up to 80% of        sales are never completed. With eCommerce, these numbers can be        far greater, and quantifying this is very difficult. For        example, a Buyer Lead may be purchased by three Sellers. When        the search terminates, the Buyer is given the opportunity to        explain why. If the reason is the product or service was        purchased from one of the Sellers, the other two have, be        definition, lost the sale. Using the Persistent Search Engine to        quantify this in real time and permit Sellers to make        adjustments accordingly creates new, unique ways to position        products and services. When combined with Unsolicited Offers and        Questionnaires, Sellers have the opportunity to, for example,        get the Buyer's business for servicing a car even though the        sale was lost to a competitor. A service relationship increases        the chances of a car sale to this Buyer next time. Of course,        this same information can be sold to other firms just looking        for new service customers.    -   11. “RSS” Buyer Data can be sold for a fee in real time as a new        type of marketing RSS news feed. Accurate marketing data is        becoming more and more expensive and always has a confidence        factor. Marketing intelligence on real Buyers looking for real        products and services has the opportunity to revolutionize        market research.    -   12. “Replay the Tape” Simulations. eCommerce can be thought of        as a continuous stream of Buyer and Seller interaction that can        be logged. This can be sold and then be replayed with different        product and service features to simulate what might have        happened under different circumstances. In this example, new or        even non-existent product or service variations can be tested        against real Buyer unfulfilled demand scenarios.    -   13. Research Questionnaires can be sent to Buyers showing        certain purchase intent or characteristics. Assured privacy and        the capability to search for real Buyers greatly increases the        quality of Questionnaire recipients and the value of the        resulting Research. Participating Buyers can be paid in the same        manner as for Unsolicited Offers.    -   14. Brokerage Fees may be charged based on the value of a        successful sale.    -   15. Cell Phone Notification fees may be charged to Sellers or        Buyers.    -   16. XML Linkage fees can be charged for using the Persistent        Search Engine to add a “persistence layer” to an existing brand.    -   17. Unfulfilled Demand Statistics can be automatically tabulated        and offered for sale. Some of these could be for product or        services that do not yet exist. For example, Buyers could have        searched for a Camry with side airbags years before it was        offered. These raw, unfulfilled demand statistics are        potentially valuable for both car manufacturer planners as well        as car dealers selling competitive products.

Examples of how revenue models may be combined:

-   -   For aggressive Seller adoption: Broadcast Buyer Leads can be        sent in a daily e-mail for free letting, say, car dealers review        them. The dealer would then be charged the full amount of the        Buyer Lead when the first Message is sent to a Buyer. The        Seller's account could be credited with $100 to offset the cost        of initial leads.    -   More typical: a base Subscription fee can be charged to Sellers,        along with a charge for each Buyer Lead, a charge for each        Quantified Lost Sales, and a premium charge for salvaging        potentially lost business with Unsolicited Offers and        Questionnaires.

It should be noted that these revenue models are driven by what a Buyerwants and not his or her identity, where they live, their race, or anyother personal information. The design of the Persistent Search Engineprotects Buyer and, if necessary, Seller identities by never requiringpersonal information to be entered.

Referring now to FIG. 28, a modeling tool that accepts a promotioncriteria and budget for unsolicited offers (revenue model #8) is shown.It then accesses high-propensity buyers for the most efficient use ofpromotion budget. This is a combination of search relevance and thevalue of the buyer's time. For example, the promotion can reach twice asmany people who want $10 than those who want $20 for the time requiredto review the offer. This process repeats until the promotional budgetis used. Different criteria and budgets can be entered until the optimaluse of the funds is determined, and them the promotion is executed.

More specifically, promotion criteria are accepted in block 2900, apromotion budget is accepted in block 2902 and searches are located bypromotion criteria in block 2904. If the promotion budget can afford thenext search result, as determined in decision block 2906, the promotionfee for the search result is subtracted in block 2908, the search resultis selected for the promotion in block 2910 and the process loops backto decision block 2906 to check the next search result. If, however, thepromotion budget cannot afford the next search result, as determined indecision block 2906, and the promotion is not optimal, as determined indecision block 2912, the process loops back to block 2900 where newpromotion criteria are accepted. If, however, the promotion is optimal,as determined in decision block 2912, the promotions are sent to theselected search results in block 2914.

Now referring to FIG. 29, a flow chart for accepting a replay criteria(search and time period) and then “replaying the tape” of buyer searchesagainst seller searches to find buyers, the latter of which can bemodified to simulate different results is shown. The process begins byaccepting replay criteria in block 3000. Thereafter, searches areidentified for replay in block 3002, the searches are replayed in block3004 and the replay results are recorded in block 3006.

Referring now to FIG. 30, a flow chart that permits the simulation torepeat looking for optimal or pre-stated results is shown. The processbegins by accepting replay criteria in block 3102. Thereafter, searchesare identified for replay in block 3004 and the searches are replayed inblock 3006. If the replay results are not optimal, as determined indecision block 3108, the process loops back to block 3106 where thesearches are replayed. If, however, the replay results are optimal, asdetermined in decision block 3108, the replay results are recorded inblock 3110.

FIGS. 31-32 are examples of screen displays for a cell phone inaccordance with one embodiment of the present invention. FIG. 33 is anexample of screen displays for an iPod in accordance with one embodimentof the present invention.

It will be understood by those of skill in the art that information andsignals may be represented using any of a variety of differenttechnologies and techniques (e.g., data, instructions, commands,information, signals, bits, symbols, and chips may be represented byvoltages, currents, electromagnetic waves, magnetic fields or particles,optical fields or particles, or any combination thereof). Likewise, thevarious illustrative logical blocks, modules, circuits, and algorithmsteps described herein may be implemented as electronic hardware,computer software, or combinations of both, depending on the applicationand functionality. Moreover, the various logical blocks, modules, andcircuits described herein may be implemented or performed with a generalpurpose processor (e.g., microprocessor, conventional processor,controller, microcontroller, state machine or combination of computingdevices), a digital signal processor (“DSP”), an application specificintegrated circuit (“ASIC”), a field programmable gate array (“FPGA”) orother programmable logic device, discrete gate or transistor logic,discrete hardware components, or any combination thereof designed toperform the functions described herein. Similarly, steps of a method orprocess described herein may be embodied directly in hardware, in asoftware module executed by a processor, or in a combination of the two.A software module may reside in RAM memory, flash memory, ROM memory,EPROM memory, EEPROM memory, registers, hard disk, a removable disk, aCD-ROM, or any other form of storage medium known in the art. Althoughpreferred embodiments of the present invention have been described indetail, it will be understood by those skilled in the art that variousmodifications can be made therein without departing from the spirit andscope of the invention as set forth in the appended claims.

What is claimed is:
 1. A non-transitory computer readable medium forelectronically searching for an item comprising program instructionswhen executed by a processor causes the processor to perform the stepsof: accessing a search index comprising a set of predefined categories,wherein each predefined category is defined by a taxonomy of attributescomprising a set of predefined attributes, wherein each predefinedattribute is defined by at least one question and one or more answers toeach question; receiving a search request for the item from a user,wherein the search request comprises a requested category for the itemselected from the set of predefined item categories, and one or morerequested attributes of the item selected from the set of predefinedattributes by providing at least one of the answers to at least one ofthe questions defining the requested attribute of the item; storing thesearch request for the item in the search index based on the requestedcategory for the item and the requested attribute(s) of the item;searching the search index for any previously stored search requestsfrom other users that match the requested category and the requestedattribute(s); determining a result of the search; sending a searchresponse comprising the result of the search; persistently searching thesearch index for the item by monitoring the search index for a triggerevent until the search request is terminated; whenever the trigger eventis detected, searching the search index for any stored search resultsthat match the requested category and the requested attributes, anddetermining a new result of the search; whenever the new result differsfrom the result, sending an updated search response comprising the newresult of the search; determining a relevancy score for each foundstored search request; wherein the step of determining the relevancyscore for each found stored result comprises the step of summing therelevancy scores for each requested attribute in the search requestdivided by the number of requested attributes in the search request; andwherein the relevancy score for each requested attribute comprises afirst value whenever the requested attribute is not specified in thestored search request, a second value whenever the requested attributematches the attribute of the stored search request and the requestedattribute is Must Have, a third value whenever the requested attributethat matches the attribute of the stored search request and therequested attribute is not Must Have, a fourth value whenever therequested attribute that does not match the attribute of the storedsearch request and the requested attribute is Must Have, and a fifthvalue whenever the requested attribute does not match the attribute ofthe stored search request and the requested attribute is not Must Have.2. The non-transitory computer readable medium as recited in claim 1,further comprising the step of creating the search request by selectingthe requested category for the item from the set of predefined itemcategories and selecting the requested attributes for the item from theset of predefined attributes for the item by providing the at least oneanswer to the at least one question defining the requested attribute ofthe item.
 3. The non-transitory computer readable medium as recited inclaim 2, wherein the requested attributes are selected using one or moredrop down boxes, one or more check boxes, one or more radio buttons, oneor more thumbnail pictures or videos, voice recognition, a fuzzy logicalgorithm, or a neural network.
 4. The non-transitory computer readablemedium as recited in claim 1, wherein the search request is initiatedfrom a presentation layer, a persistence layer, or a brand layer.
 5. Thenon-transitory computer readable medium as recited in claim 1, whereinthe at least one question and the one or more answers to each questionthat define each attribute differ based on a language, a culture or aregion associated with the search request.
 6. The non-transitorycomputer readable medium as recited in claim 5, wherein the search indexis capable of providing matches regardless of the language, the cultureor the region associated with the search request.
 7. The non-transitorycomputer readable medium as recited in claim 1, wherein the searchrequest further comprises a price, a price range, a description, one ormore comments, one or more keywords, or a minimum feedback score for theother user associated with any found stored search request.
 8. Thenon-transitory computer readable medium as recited in claim 7, furthercomprising the step of storing the price, the price range, thedescription, the comments, the keywords, the minimum feedback score orthe combination thereof in the search index or in a data storage.
 9. Thenon-transitory computer readable medium as recited in claim 1, whereinthe item comprises a product, a service, a topic, a classified-typeadvertisement, or a personal-type advertisement.
 10. The non-transitorycomputer readable medium as recited in claim 1, wherein one of: eachstored search request relates to an item posted for advertisement,exchange, lease, sale, trade or transfer by the user that submitted thestored search request; each stored search request relates to an itemsought by the user that submitted the stored search request foradvertisement, exchange, lease, sale, trade or transfer; each storedsearch request comprises information posted about an item provided bythe user that submitted the stored search request; and each storedsearch request comprises information about an item sought by the userthat submitted the stored search request.
 11. The non-transitorycomputer readable medium as recited in claim 1, wherein one of: thereceived search request relates to an item posted for advertisement,exchange, lease, sale, trade or transfer by the user that submitted thereceived search request; the received search request relates to an itemsought by the user that submitted the received search request foradvertisement, exchange, lease, sale, trade or transfer; the receivedsearch request comprises information posted about an item provided bythe user that submitted the received search request; the received searchrequest comprises information about an item sought by the user thatsubmitted the received search request; the received search requestcomprises a search for posted items that satisfy one or more criteria;the received search request comprises a search for sought items thatsatisfy one or more criteria; the received search request comprises asearch for sought attributes; the received search request comprises asearch for sought information; the received search request comprises abulk search; the received search request comprises a search for closehits that satisfy one or more criteria; and the received search requestcomprises a search for lost sales that satisfy one or more criteria. 12.The non-transitory computer readable medium as recited in claim 1,wherein the search request is submitted by one of: a buyer, a seller, abuyer/seller, a “window shopper”, a researcher, and an interested user.13. The non-transitory computer readable medium as recited in claim 1,wherein the categories are grouped into one or more subject areas. 14.The non-transitory computer readable medium as recited in claim 13,wherein: the subject areas comprise one of real estate, motor vehicles,employment, financial services, residential services, professionalservices, travel, vacation, computers, entertainment, dining, dating,hobbies, electronics, furniture, tools, home improvement, officesupplies, household items, sporting goods, sporting events, recreation,or event tickets; the categories within the real estate subject areacomprise houses, apartments, land, farms, commercial, insurance, financeor moving/storage; the categories within the motor vehicles subject areacomprise cars, trucks, recreational, repairs, insurance or finance; thecategories within employment comprise administrative, professional,education, healthcare, retail or manufacturing; the categories withinfinancial services comprise mortgages, loans, brokerage accounts, mutualfunds, small business or bill pay; the categories within residentialservices comprise plumber, electrician, lawn & garden, appliance repair,remodeling or cleaning; and the categories within professional servicecomprise attorneys, accountants or computer services.
 15. Thenon-transitory computer readable medium as recited in claim 1, whereinthe trigger event is one of: a newly received search request, a changein the search request, a specified time period, receipt of an updaterequest, a change to the search index that would change the result ofthe search, and a deletion of a stored search request.
 16. Thenon-transitory computer readable medium as recited in claim 1, whereinthe search request is terminated after one of: a specified time periodhas elapsed, a specified number of searches are performed, the searchrequest is changed, deleted or terminated by the user, the searchrequest is changed, deleted or terminated by a system, and the searchrequest is replaced.
 17. The non-transitory computer readable medium asrecited in claim 1, wherein the search response is sent to a userspecified device comprising one of: a computer, a laptop, a handheldcomputer, an e-mail address, a personal data assistant, a telephone, amobile telephone, a portable media player, a portable communicationsdevice, a facsimile device, and a Web-enabled device.
 18. Thenon-transitory computer readable medium as recited in claim 1, whereinthe stored search request does not contain any personal informationrelating to the user that submitted the stored search request or onlycontains personal information added by the user that submitted thestored search request.
 19. The non-transitory computer readable mediumas recited in claim 1, further comprising the step of removing anypersonal information from the received search request relating to theuser that submitted the received search request or providing a warningto the user that submitted the received search request before thereceived search request is stored in the search index.
 20. Thenon-transitory computer readable medium as recited in claim 1, whereinthe stored search requests match the requested category and therequested attribute(s) whenever: the attributes of the stored searchrequests are equal to or exceed the requested attributes; the attributesof the stored search requests are substantially similar to the requestedattributes; the attributes of the stored search requests are within arange of the requested attributes; or a relevancy score for the storedsearch requests is satisfied.
 21. The non-transitory computer readablemedium as recited in claim 1, wherein the step of searching the searchindex is halted after a specified number of matches have been found. 22.The non-transitory computer readable medium as recited in claim 1,further comprising the step of updating the search index whenever astored search request is added, changed or deleted.
 23. Thenon-transitory computer readable medium as recited in claim 1, furthercomprising the step of displaying the relevancy score graphically. 24.The non-transitory computer readable medium as recited in claim 1,wherein the determination of the relevancy score is based on one of: oneor more user preferences, a closeness of the requested attributes in thesearch request to the attributes of the stored search request, adistance between an item associated with a stored search request and alocation of the user, and a user specified budget.
 25. Thenon-transitory computer readable medium as recited in claim 1, furthercomprising the step of providing the relevancy score to the userassociated with the stored search request, or another interested user.26. The non-transitory computer readable medium as recited in claim 1,further comprising the step of receiving one or more preferencesassociated with the user or the search request.
 27. The non-transitorycomputer readable medium as recited in claim 26, wherein the one or morepreferences comprise one of: an urgency, a results per screen, anminimum required relevancy limit, a minimum required rating associatedwith the stored search request, one or more user devices that are to beused for communications, and one or more messaging limits.
 28. Thenon-transitory computer readable medium as recited in claim 1, furthercomprising the step of sending a notification to the user whenever: therequested attributes of a received search request matches a storedsearch request associated with the user; a received search request ischanged that previously matched the stored search request associatedwith the user; a received search request is changed that now matches thestored search request associated with the user; an item associated witha stored search request is located within a specified distance from alocation of the user; the result of the search request by the user haschanged; the result of the search request by the user has not changed;or a relevancy score for the stored search requests is satisfied. 29.The non-transitory computer readable medium as recited in claim 28,wherein the notification comprises one of: a request to return to thestored search request or the result of the search, a link to return tothe stored search request or the result of the search, a description ofa reason for the notification, a message, and a new search request. 30.The non-transitory computer readable medium as recited in claim 1,further comprising the step of providing a messaging system between theuser that submitted the search request and each user associated with thestored search requests that matched the requested attributes.
 31. Thenon-transitory computer readable medium as recited in claim 30, whereinthe messages within the messaging system are private between the userthat submitted the search request and each user associated with thestored search requests that matched the requested attributes and cannotbe accessed by third parties.
 32. The non-transitory computer readablemedium as recited in claim 30, wherein the messages within the messagingsystem do not contain any personal information about the user thatsubmitted the search request and each user associated with the storedsearch requests that matched the requested attributes unless suchpersonal information is added by one of the users.
 33. Thenon-transitory computer readable medium as recited in claim 30, whereinthe messages within the messaging system are not tied to a mail serveror an e-mail address.
 34. The non-transitory computer readable medium asrecited in claim 30, wherein the messages are logged and tied to thesearch request.
 35. The non-transitory computer readable medium asrecited in claim 30, wherein the user that submitted the search requestand each user associated with the stored search requests that matchedthe requested attributes can specify a limit on the number of messagesthat another user can send to them.
 36. The non-transitory computerreadable medium as recited in claim 30, wherein the user can add anattachment or additional content to the messages within the messagingsystem if the attachment satisfies one or more criteria.
 37. Thenon-transitory computer readable medium as recited in claim 30, whereinthe user can accept unsolicited offers, unsolicited messages,questionnaires, advertisements or a combination thereof if such offers,messages, questionnaires or advertisements satisfy one or more criteria.38. The non-transitory computer readable medium as recited in claim 1,further comprising the steps of: receiving feedback or commentsregarding the user or a stored search request; and associating thefeedback or comments with the user or the stored search request.
 39. Thenon-transitory computer readable medium as recited in claim 1, furthercomprising the step of authenticating the received search request. 40.The non-transitory computer readable medium as recited in claim 1,wherein the steps of storing the search request, searching the searchindex, determining the result of the search and sending the searchresponse are performed at a level of functionality associated with theuser associated with the received search request.
 41. The non-transitorycomputer readable medium as recited in claim 1, further comprising thestep of resubmitting a previously submitted search request.
 42. Thenon-transitory computer readable medium as recited in claim 1, furthercomprising the step of linking information contained in a legacydatabase to the search index.
 43. The non-transitory computer readablemedium as recited in claim 146, wherein the information is linked via anXML or EDI index, loaded into the search index, or loaded and indexedinto a data storage.
 44. The non-transitory computer readable medium asrecited in claim 1, further comprising the step of deleting a storedsearch request.
 45. An apparatus for electronically searching for anitem comprising: a computer having a processor communicably coupled to adata storage; a search index stored in the data storage comprising a setof predefined categories, wherein each predefined category is defined bya taxonomy of attributes comprising a set of predefined attributes,wherein each predefined attribute is defined by at least one questionand one or more answers to each question; and a search engine executableby the processor that causes the processor to: (a) receive a searchrequest for the item from a user, wherein the search request comprises arequested category for the item selected from the set of predefined itemcategories, and one or more requested attributes of the item selectedfrom the set of predefined attributes by providing at least one of theanswers to at least one of the questions defining the requestedattribute of the item; (b) store the search request for the item in thesearch index based on the requested category for the item and therequested attribute(s) for the item; (c) search the search index for anypreviously stored search requests from other users that match therequested category and the requested attribute(s); (d) determine aresult of the search; (e) send a search response comprising the resultof the search; (f) persistently search the search index for the item bymonitoring the search index for a trigger event until the search requestis terminated; (g) whenever the trigger event is detected, search thesearch index for any stored search results that match the requestedcategory and the requested attributes, and determine a new result of thesearch; (h) whenever the new result differs from the result, send anupdated search response comprising the new result of the search; (i)determining a relevancy score for each found stored search request:wherein the step of determining the relevancy score for each foundstored result comprises the step of summing the relevancy scores foreach requested attribute in the search request divided by the number ofrequested attributes in the search request; wherein the relevancy scorefor each requested attribute comprises a first value whenever therequested attribute is not specified in the stored search request, asecond value whenever the requested attribute matches the attribute ofthe stored search request and the requested attribute is Must Have, athird value whenever the requested attribute that matches the attributeof the stored search request and the requested attribute is not MustHave, a fourth value whenever the requested attribute that does notmatch the attribute of the stored search request and the requestedattribute is Must Have, and a fifth value whenever the requestedattribute does not match the attribute of the stored search request andthe requested attribute is not Must Have.
 46. The apparatus as recitedin claim 45, wherein the search engine further creates the searchrequest by selecting the requested category for the item from the set ofpredefined item categories and selects the requested attributes for theitem from the set of predefined attributes for the item by providing theat least one answer to the at least one question defining the requestedattribute of the item.
 47. The apparatus as recited in claim 46, whereinthe requested attributes are selected using one or more drop down boxes,one or more check boxes, one or more radio buttons, one or morethumbnail pictures or videos, voice recognition, a fuzzy logicalgorithm, or a neural network.
 48. The apparatus as recited in claim45, wherein the search request is initiated from a presentation layer, apersistence layer, or a brand layer.
 49. The apparatus as recited inclaim 45, wherein the at least one question and the one or more answersto each question that define each attribute differ based on a language,a culture or a region associated with the search request.
 50. Theapparatus as recited in claim 49, wherein the search index is capable ofproviding matches regardless of the language, the culture or the regionassociated with the search request.
 51. The apparatus as recited inclaim 45, wherein the search request further comprises a price, a pricerange, a description, one or more comments, one or more keywords, or aminimum feedback score for the other user associated with any foundstored search request.
 52. The apparatus as recited in claim 51, whereinthe search engine further stories the price, the price range, thedescription, the comments, the keywords, the minimum feedback score orthe combination thereof in the search index or in a data storage. 53.The apparatus as recited in claim 45, wherein the item comprises aproduct, a service, a topic, a classified-type advertisement, or apersonal-type advertisement.
 54. The apparatus as recited in claim 45,wherein one of: each stored search request relates to an item posted foradvertisement, exchange, lease, sale, trade or transfer by the user thatsubmitted the stored search request; each stored search request relatesto an item sought by the user that submitted the stored search requestfor advertisement, exchange, lease, sale, trade or transfer; each storedsearch request comprises information posted about an item provided bythe user that submitted the stored search request; and each storedsearch request comprises information about an item sought by the userthat submitted the stored search request.
 55. The apparatus as recitedin claim 45, wherein one of: the received search request relates to anitem posted for advertisement, exchange, lease, sale, trade or transferby the user that submitted the received search request; the receivedsearch request relates to an item sought by the user that submitted thereceived search request for advertisement, exchange, lease, sale, tradeor transfer; the received search request comprises information postedabout an item provided by the user that submitted the received searchrequest; the received search request comprises information about an itemsought by the user that submitted the received search request; thereceived search request comprises a search for posted items that satisfyone or more criteria; the received search request comprises a search forsought items that satisfy one or more criteria; the received searchrequest comprises a search for sought attributes; the received searchrequest comprises a search for sought information; the received searchrequest comprises a bulk search; the received search request comprises asearch for close hits that satisfy one or more criteria; and thereceived search request comprises a search for lost sales that satisfyone or more criteria.
 56. The apparatus as recited in claim 45, whereinthe search request is submitted by one of: a buyer, a seller, abuyer/seller, a “window shopper”, a researcher, and an interested user.57. The apparatus as recited in claim 45, wherein the categories aregrouped into one or more subject areas.
 58. The apparatus as recited inclaim 57, wherein: the subject areas comprise one of real estate, motorvehicles, employment, financial services, residential services,professional services, travel, vacation, computers, entertainment,dining, dating, hobbies, electronics, furniture, tools, homeimprovement, office supplies, household items, sporting goods, sportingevents, recreation, or event tickets; the categories within the realestate subject area comprise houses, apartments, land, farms,commercial, insurance, finance or moving/storage; the categories withinthe motor vehicles subject area comprise cars, trucks, recreational,repairs, insurance or finance; the categories within employment compriseadministrative, professional, education, healthcare, retail ormanufacturing; the categories within financial services comprisemortgages, loans, brokerage accounts, mutual funds, small business orbill pay; the categories within residential services comprise plumber,electrician, lawn & garden, appliance repair, remodeling or cleaning;and the categories within professional service comprise attorneys,accountants or computer services.
 59. The apparatus as recited in claim45, wherein the trigger event is one of: a newly received searchrequest, a change in the search request, a specified time period,receipt of an update request, a change to the search index that wouldchange the result of the search, and a deletion of a stored searchrequest.
 60. The apparatus as recited in claim 45, wherein the searchrequest is terminated after one of: a specified time period has elapsed,a specified number of searches are performed, the search request ischanged, deleted or terminated by the user, the search request ischanged, deleted or terminated by a apparatus, and the search request isreplaced.
 61. The apparatus as recited in claim 45, wherein the searchresponse is sent to a user specified device comprising one of: acomputer, a laptop, a handheld computer, an e-mail address, a personaldata assistant, a telephone, a mobile telephone, a portable mediaplayer, a portable communications device, a facsimile device, and aWeb-enabled device.
 62. The apparatus as recited in claim 45, whereinthe stored search request does not contain any personal informationrelating to the user that submitted the stored search request or onlycontains personal information added by the user that submitted thestored search request.
 63. The apparatus as recited in claim 45, whereinthe search engine further removes any personal information from thereceived search request relating to the user that submitted the receivedsearch request or providing a warning to the user that submitted thereceived search request before the received search request is stored inthe search index.
 64. The apparatus as recited in claim 45, wherein thestored search requests match the requested category and the requestedattribute(s) whenever: the attributes of the stored search requests areequal to or exceed the requested attributes; the attributes of thestored search requests are substantially similar to the requestedattributes; the attributes of the stored search requests are within arange of the requested attributes; or a relevancy score for the storedsearch requests is satisfied.
 65. The apparatus as recited in claim 45,wherein the search engine halts searching the search index after aspecified number of matches have been found.
 66. The apparatus asrecited in claim 45, wherein the search engine further updates thesearch index whenever a stored search request is added, changed ordeleted.
 67. The apparatus as recited in claim 45, wherein the searchengine further displays the relevancy score graphically.
 68. Theapparatus as recited in claim 45, wherein the determination of therelevancy score is based on one of: one or more user preferences, acloseness of the requested attributes in the search request to theattributes of the stored search request, a distance between an itemassociated with a stored search request and a location of the user, anda user specified budget.
 69. The apparatus as recited in claim 45,wherein the search engine further provides the relevancy score to theuser associated with the stored search request, or another interesteduser.
 70. The apparatus as recited in claim 45, wherein the searchengine further receives one or more preferences associated with the useror the search request.
 71. The apparatus as recited in claim 70, whereinthe one or more preferences comprise one of: an urgency, a results perscreen, an minimum required relevancy limit, a minimum required ratingassociated with the stored search request, one or more user devices thatare to be used for communications, and one or more messaging limits. 72.The apparatus as recited in claim 45, wherein the search engine furthersends a notification to the user whenever: the requested attributes of areceived search request matches a stored search request associated withthe user; a received search request is changed that previously matchedthe stored search request associated with the user; a received searchrequest is changed that now matches the stored search request associatedwith the user; an item associated with a stored search request islocated within a specified distance from a location of the user; theresult of the search request by the user has changed; the result of thesearch request by the user has not changed; or a relevancy score for thestored search requests is satisfied.
 73. The apparatus as recited inclaim 72, wherein the notification comprises one of: a request to returnto the stored search request or the result of the search, a link toreturn to the stored search request or the result of the search, adescription of a reason for the notification, a message, and a newsearch request.
 74. The apparatus as recited in claim 45, wherein thesearch engine further provides a messaging system between the user thatsubmitted the search request and each user associated with the storedsearch requests that matched the requested attributes.
 75. The apparatusas recited in claim 74, wherein the messages within the messaging systemare private between the user that submitted the search request and eachuser associated with the stored search requests that matched therequested attributes and cannot be accessed by third parties.
 76. Theapparatus as recited in claim 74, wherein the messages within themessaging system do not contain any personal information about the userthat submitted the search request and each user associated with thestored search requests that matched the requested attributes unless suchpersonal information is added by one of the users.
 77. The apparatus asrecited in claim 74, wherein the messages within the messaging systemare not tied to a mail server or an e-mail address.
 78. The apparatus asrecited in claim 74, wherein the messages are logged and tied to thesearch request.
 79. The apparatus as recited in claim 74, wherein theuser that submitted the search request and each user associated with thestored search requests that matched the requested attributes can specifya limit on the number of messages that another user can send to them.80. The apparatus as recited in claim 74, wherein the user can add anattachment or additional content to the messages within the messagingsystem if the attachment satisfies one or more criteria.
 81. Theapparatus as recited in claim 74, wherein the user can acceptunsolicited offers, unsolicited messages, questionnaires, advertisementsor a combination thereof if such offers, messages, questionnaires oradvertisements satisfy one or more criteria.
 82. The apparatus asrecited in claim 45, wherein the search engine further: receivesfeedback or comments regarding the user or a stored search request; andassociates the feedback or comments with the user or the stored searchrequest.
 83. The apparatus as recited in claim 45, wherein the searchengine further authenticates the received search request.
 84. Theapparatus as recited in claim 45, wherein the steps of storing thesearch request, searching the search index, determining the result ofthe search and sending the search response are performed at a level offunctionality associated with the user associated with the receivedsearch request.
 85. The apparatus as recited in claim 45, wherein thesearch engine further resubmits a previously submitted search request.86. The apparatus as recited in claim 45, wherein the search enginefurther links information contained in a legacy database to the searchindex.
 87. The apparatus as recited in claim 86, wherein the informationis linked via an XML or EDI index, loaded into the search index, orloaded and indexed into a data storage.
 88. The apparatus as recited inclaim 45, wherein the search engine further deletes a stored searchrequest.
 89. A system for electronically searching for an itemcomprising: a network; a search index communicably coupled to thenetwork comprising a set of predefined categories, wherein eachpredefined category is defined by a taxonomy of attributes comprising aset of predefined attributes, wherein each predefined attribute isdefined by at least one question and one or more answers to eachquestion; one or more user devices communicably coupled to the network;a user interface communicably coupled to the network for entering asearch request from a user and receiving a search response, wherein thesearch request comprises a requested category for the item selected fromthe set of predefined item categories, and one or more requestedattributes of the item selected from the set of predefined attributes byproviding at least one of the answers to at least one of the questionsdefining the requested attribute of the item; and a search enginecommunicably coupled to the user interface and the search index via thenetwork wherein the search engine: (a) receives the search request forthe item; (b) stores the search request for the item in the search indexbased on the requested category for the item and the requestedattribute(s) for the item; (c) searches the search index for anypreviously stored search requests from other users that match therequested category and the requested attribute(s); (d) determines theresult of the search; (e) sends the result of the search; (f)persistently searches the search index for the item by monitoring thesearch index for a trigger event until the search request is terminated;(g) whenever the trigger event is detected, searches the search indexfor any stored search results that match the requested category and therequested attributes, and determines a new result of the search; (h)whenever the new result differs from the result, sends an updated searchresponse comprising the new result of the search (i) determining arelevancy score for each found stored search request: wherein the stepof determining the relevancy score for each found stored resultcomprises the step of summing the relevancy scores for each requestedattribute in the search request divided by the number of requestedattributes in the search request; wherein the relevancy score for eachrequested attribute comprises a first value whenever the requestedattribute is not specified in the stored search request, a second valuewhenever the requested attribute matches the attribute of the storedsearch request and the requested attribute is Must Have, a third valuewhenever the requested attribute that matches the attribute of thestored search request and the requested attribute is not Must Have, afourth value whenever the requested attribute that does not match theattribute of the stored search request and the requested attribute isMust Have, and a fifth value whenever the requested attribute does notmatch the attribute of the stored search request and the requestedattribute is not Must Have.
 90. The system as recited in claim 89,wherein the search engine further creates the search request byselecting the requested category for the item from the set of predefineditem categories and selects the requested attributes for the item fromthe set of predefined attributes for the item by providing the at leastone answer to the at least one question defining the requested attributeof the item.
 91. The system as recited in claim 90, wherein therequested attributes are selected using one or more drop down boxes, oneor more check boxes, one or more radio buttons, one or more thumbnailpictures or videos, voice recognition, a fuzzy logic algorithm, or aneural network.
 92. The system as recited in claim 89, wherein thesearch request is initiated from a presentation layer, a persistencelayer, or a brand layer.
 93. The system as recited in claim 89, whereinthe at least one question and the one or more answers to each questionthat define each attribute differ based on a language, a culture or aregion associated with the search request.
 94. The system as recited inclaim 93, wherein the search index is capable of providing matchesregardless of the language, the culture or the region associated withthe search request.
 95. The system as recited in claim 89, wherein thesearch request further comprises a price, a price range, a description,one or more comments, one or more keywords, or a minimum feedback scorefor the other user associated with any found stored search request. 96.The system as recited in claim 95, wherein the search engine furtherstories the price, the price range, the description, the comments, thekeywords, the minimum feedback score or the combination thereof in thesearch index or in a data storage.
 97. The system as recited in claim89, wherein the item comprises a product, a service, a topic, aclassified-type advertisement, or a personal-type advertisement.
 98. Thesystem as recited in claim 89, wherein one of: each stored searchrequest relates to an item posted for advertisement, exchange, lease,sale, trade or transfer by the user that submitted the stored searchrequest; each stored search request relates to an item sought by theuser that submitted the stored search request for advertisement,exchange, lease, sale, trade or transfer; each stored search requestcomprises information posted about an item provided by the user thatsubmitted the stored search request; and each stored search requestcomprises information about an item sought by the user that submittedthe stored search request.
 99. The system as recited in claim 89,wherein one of: the received search request relates to an item postedfor advertisement, exchange, lease, sale, trade or transfer by the userthat submitted the received search request; the received search requestrelates to an item sought by the user that submitted the received searchrequest for advertisement, exchange, lease, sale, trade or transfer; thereceived search request comprises information posted about an itemprovided by the user that submitted the received search request; thereceived search request comprises information about an item sought bythe user that submitted the received search request; the received searchrequest comprises a search for posted items that satisfy one or morecriteria; the received search request comprises a search for soughtitems that satisfy one or more criteria; the received search requestcomprises a search for sought attributes; the received search requestcomprises a search for sought information; the received search requestcomprises a bulk search; the received search request comprises a searchfor close hits that satisfy one or more criteria; and the receivedsearch request comprises a search for lost sales that satisfy one ormore criteria.
 100. The system as recited in claim 89, wherein thesearch request is submitted by one of: a buyer, a seller, abuyer/seller, a “window shopper”, a researcher, and an interested user.101. The system as recited in claim 89, wherein the categories aregrouped into one or more subject areas.
 102. The system as recited inclaim 101, wherein: the subject areas comprise one of real estate, motorvehicles, employment, financial services, residential services,professional services, travel, vacation, computers, entertainment,dining, dating, hobbies, electronics, furniture, tools, homeimprovement, office supplies, household items, sporting goods, sportingevents, recreation, or event tickets; the categories within the realestate subject area comprise houses, apartments, land, farms,commercial, insurance, finance or moving/storage; the categories withinthe motor vehicles subject area comprise cars, trucks, recreational,repairs, insurance or finance; the categories within employment compriseadministrative, professional, education, healthcare, retail ormanufacturing; the categories within financial services comprisemortgages, loans, brokerage accounts, mutual funds, small business orbill pay; the categories within residential services comprise plumber,electrician, lawn & garden, appliance repair, remodeling or cleaning;and the categories within professional service comprise attorneys,accountants or computer services.
 103. The system as recited in claim89, wherein the trigger event is one of: a newly received searchrequest, a change in the search request, a specified time period,receipt of an update request, a change to the search index that wouldchange the result of the search, and a deletion of a stored searchrequest.
 104. The system as recited in claim 89, wherein the searchrequest is terminated after one of: a specified time period has elapsed,a specified number of searches are performed, the search request ischanged, deleted or terminated by the user, the search request ischanged, deleted or terminated by a system, and the search request isreplaced.
 105. The system as recited in claim 89, wherein the searchresponse is sent to a user specified device comprising one of: acomputer, a laptop, a handheld computer, an e-mail address, a personaldata assistant, a telephone, a mobile telephone, a portable mediaplayer, a portable communications device, a facsimile device, and aWeb-enabled device.
 106. The system as recited in claim 89, wherein thestored search request does not contain any personal information relatingto the user that submitted the stored search request or only containspersonal information added by the user that submitted the stored searchrequest.
 107. The system as recited in claim 89, wherein the searchengine further removes any personal information from the received searchrequest relating to the user that submitted the received search requestor providing a warning to the user that submitted the received searchrequest before the received search request is stored in the searchindex.
 108. The system as recited in claim 89, wherein the stored searchrequests match the requested category and the requested attribute(s)whenever: the attributes of the stored search requests are equal to orexceed the requested attributes; the attributes of the stored searchrequests are substantially similar to the requested attributes; theattributes of the stored search requests are within a range of therequested attributes; or a relevancy score for the stored searchrequests is satisfied.
 109. The system as recited in claim 89, whereinthe search engine halts searching the search index after a specifiednumber of matches have been found.
 110. The system as recited in claim89, wherein the search engine further updates the search index whenevera stored search request is added, changed or deleted.
 111. The system asrecited in claim 89, wherein the search engine further displays therelevancy score graphically.
 112. The system as recited in claim 89,wherein the determination of the relevancy score is based on one of: oneor more user preferences, a closeness of the requested attributes in thesearch request to the attributes of the stored search request, adistance between an item associated with a stored search request and alocation of the user, and a user specified budget.
 113. The system asrecited in claim 89, wherein the search engine further provides therelevancy score to the user associated with the stored search request,or another interested user.
 114. The system as recited in claim 89,wherein the search engine further receives one or more preferencesassociated with the user or the search request.
 115. The system asrecited in claim 114, wherein the one or more preferences comprise oneof: an urgency, a results per screen, an minimum required relevancylimit, a minimum required rating associated with the stored searchrequest, one or more user devices that are to be used forcommunications, and one or more messaging limits.
 116. The system asrecited in claim 89, wherein the search engine further sends anotification to the user whenever: the requested attributes of areceived search request matches a stored search request associated withthe user; a received search request is changed that previously matchedthe stored search request associated with the user; a received searchrequest is changed that now matches the stored search request associatedwith the user; an item associated with a stored search request islocated within a specified distance from a location of the user; theresult of the search request by the user has changed; the result of thesearch request by the user has not changed; or a relevancy score for thestored search requests is satisfied.
 117. The system as recited in claim89, wherein the notification comprises one of: a request to return tothe stored search request or the result of the search, a link to returnto the stored search request or the result of the search, a descriptionof a reason for the notification, a message, and a new search request.118. The system as recited in claim 89, wherein the search enginefurther provides a messaging system between the user that submitted thesearch request and each user associated with the stored search requeststhat matched the requested attributes.
 119. The system as recited inclaim 118, wherein the messages within the messaging system are privatebetween the user that submitted the search request and each userassociated with the stored search requests that matched the requestedattributes and cannot be accessed by third parties.
 120. The system asrecited in claim 118, wherein the messages within the messaging systemdo not contain any personal information about the user that submittedthe search request and each user associated with the stored searchrequests that matched the requested attributes unless such personalinformation is added by one of the users.
 121. The system as recited inclaim 118, wherein the messages within the messaging system are not tiedto a mail server or an e-mail address.
 122. The system as recited inclaim 118, wherein the messages are logged and tied to the searchrequest.
 123. The system as recited in claim 118, wherein the user thatsubmitted the search request and each user associated with the storedsearch requests that matched the requested attributes can specify alimit on the number of messages that another user can send to them. 124.The system as recited in claim 118, wherein the user can add anattachment or additional content to the messages within the messagingsystem if the attachment satisfies one or more criteria.
 125. The systemas recited in claim 118, wherein the user can accept unsolicited offers,unsolicited messages, questionnaires, advertisements or a combinationthereof if such offers, messages, questionnaires or advertisementssatisfy one or more criteria.
 126. The system as recited in claim 89,wherein the search engine further: receives feedback or commentsregarding the user or a stored search request; and associates thefeedback or comments with the user or the stored search request. 127.The system as recited in claim 89, wherein the search engine furtherauthenticates the received search request.
 128. The system as recited inclaim 89, wherein the steps of storing the search request, searching thesearch index, determining the result of the search and sending thesearch response are performed at a level of functionality associatedwith the user associated with the received search request.
 129. Thesystem as recited in claim 89, wherein the search engine furtherresubmits a previously submitted search request.
 130. The system asrecited in claim 89, wherein the search engine further links informationcontained in a legacy database to the search index.
 131. The system asrecited in claim 130, wherein the information is linked via an XML orEDI index, loaded into the search index, or loaded and indexed into adata storage.
 132. The system as recited in claim 89, wherein the searchengine further deletes a stored search request.